Age at death is one of the key elements of the“biological profile"prepared when analysing unidentified human remains.Biological age is determined according to physiological indicators and developmental stage,whi...Age at death is one of the key elements of the“biological profile"prepared when analysing unidentified human remains.Biological age is determined according to physiological indicators and developmental stage,which can be determined by bone assessment.It is worth remembering that the researcher must interpret each case individually and in accordance with the current state of knowledge.One of the most developed tools for analysing human remains is postmortem computed tomography.This allows for the visualization not only of bones without maceration but also of the entire body under various altered states,including corpses in advanced stages of decomposition and burnt bodies.The aim of this review is to present the current methods for age estimation based on postmortem computed tomography evaluation,comparing the results presented in 18 research projects published between 2013 and 2023 on foetuses,children,and adults from contemporary populations.Recent literature includes assessment of bones and characteristics such as skulls,teeth,vertebrae,pelvises,and long bones to estimate age at death.We cover the methods used in this recent literature,including machine learning,and discuss the advantages and disadvantages of them.展开更多
This study evaluates the accuracy and reliability of the˙Iscan and Hartnett methods for estimating the age of adults based on rib analysis,using a sample of 127 pairs of ribs from a contemporary European population.T...This study evaluates the accuracy and reliability of the˙Iscan and Hartnett methods for estimating the age of adults based on rib analysis,using a sample of 127 pairs of ribs from a contemporary European population.The study employed a double-blind design with repeated measurements conducted by two observers.The˙Iscan method demonstrated a higher success rate,accurately assigning age in 62%of cases,compared to 38%for the Hartnett method.Both methods exhibited moderate intra-and interoperator agreement,as measured by Cohen’s Kappa.A detailed statistical analysis,including logistic regression,revealed significant discrepancies in phase-assignment accuracy between the two methods.The˙Iscan method’s success rate improved when prioritizing the highest observed phase,indicating potential for enhancing accuracy through strategic methodological adjustments.The findings underscore the importance of operator training and the need for consistent application of criteria.This research highlights the critical need for standardization in age estimation methods and suggests potential improvements for forensic and anthropological applications.The study contributes valuable insights into the strengths and limitations of widely used skeletal age estimation techniques,with implications for improving methodological consistency and accuracy in forensic investigations.展开更多
Age estimation of adults is a challenging procedure in forensic practice.Inspired by the previous work by Chinese scholars,we established population-specific age estimation models from the osseous and calcified projec...Age estimation of adults is a challenging procedure in forensic practice.Inspired by the previous work by Chinese scholars,we established population-specific age estimation models from the osseous and calcified projections(OCPs)of costal cartilages,using three-dimensional volume-rendering technique.A total of 168 clinical CT scans(2 mm slice thickness)were used to develop the sex-specific age prediction models from a sample of Egyptians,comprising 70 females and 98 males,with documented ages between 12 and 85 years.The sample was also used for validating the Chinese model.We reported the differences between the predictive accuracy of the Egyptian(population specific)and Chinese(non-population specific)models.The most accurate age estimation model was stepwise linear regression with standard error of estimates of 10.9 and 11.8 years in males and females,respectively.For the simple linear regression models,the most accurate formula included OCP of the right second costal cartilage in males and OCP of the left third costal cartilage in females with standard error of estimates of 11.2 and 12.2 years,respectively,and mean absolute error(MAE)of 8.8 and 9.6 years,respectively.By comparison,the best accuracy rates produced by the Chinese vs.the Egyptian models in males and females within 5 years were 30.61%and 32.86%vs.35.71%and 32.86%,respectively,whereas within 10 years,the accuracy rates increased up to 57.14%and 58.57%vs.72.45%and 64.29%,respectively.Although the accuracy rates from the Chinese models were lower than those obtained from the Egyptian models,the MAE and least error values were comparable in both sexes.Notable accurate age estimation rates in the advanced age group≥40 years were reached being 81.25%to 97.92%in males and 69.77%to 93.02%in females.OCP of the right first costal cartilage was the most accurate in cross-population application for males and females with MAE values of 10.7 and 11.03 years,respectively,with balanced accuracy rates of age estimation using the 10-year interval and 40-year cutoff.展开更多
Wound age estimation is one of the most challenging and indispensable issues for forensic pathologists.Although many methods based on physical findings and biochemical tests can be used to estimate wound age,an object...Wound age estimation is one of the most challenging and indispensable issues for forensic pathologists.Although many methods based on physical findings and biochemical tests can be used to estimate wound age,an objective and reliable method for inferring the time interval after injury remains difficult.In the present study,endogenous metabolites of contused skeletal muscle were investigated to estimate the time interval after injury.Animal model of skeletal muscle injury was established using Sprague–Dawley rat,and the contused muscles were sampled at 4,8,12,16,20,24,28,32,36,40,44,and 48 h postcontusion(n=9).Then,the samples were analysed using ultraperformance liquid chromatography coupled with high-resolution mass spectrometry.A total of 43 differential metabolites in contused muscle were determined by metabolomics method.They were applied to construct a two-level tandem prediction model for wound age estimation based on multilayer perceptron algorithm.As a result,all muscle samples were eventually divided into the following subgroups:4,8,12,16–20,24–32,36–40,and 44–48 h.The tandem model exhibited a robust performance and achieved a prediction accuracy of 92.6%,which was much higher than that of the single model.In summary,the multilayer perceptron–multilayer perceptron tandem machine-learning model based on metabolomics data can be used as a novel strategy for wound age estimation in future forensic casework.展开更多
Aiming at the problem of long time-consuming and low accuracy of existing age estimation approaches,a new age estimation method using Gabor feature fusion,and an improved atomic search algorithm for feature selection ...Aiming at the problem of long time-consuming and low accuracy of existing age estimation approaches,a new age estimation method using Gabor feature fusion,and an improved atomic search algorithm for feature selection is proposed.Firstly,texture features of five scales and eight directions in the face region are extracted by Gabor wavelet transform.The statistical histogram is introduced to encode and fuse the directional index with the largest feature value on Gabor scales.Secondly,a new hybrid feature selection algorithm chaotic improved atom search optimisation with simulated annealing(CIASO-SA)is presented,which is based on an improved atomic search algorithm and the simulated annealing algorithm.Besides,the CIASO-SA algorithm introduces a chaos mechanism during atomic initialisation,significantly improving the convergence speed and accuracy of the algorithm.Finally,a support vector machine(SVM)is used to get classification results of the age group.To verify the performance of the proposed algorithm,face images with three resolutions in the Adience dataset are tested.Using the Gabor real part fusion feature at 48�48 resolution,the average accuracy and 1-off accuracy of age classification exhibit a maximum of 60.4%and 85.9%,respectively.Obtained results prove the superiority of the proposed algorithm over the state-of-the-art methods,which is of great referential value for application to the mobile terminals.展开更多
The aim of this study was to evaluate the applicability of Cameriere’s European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children.M...The aim of this study was to evaluate the applicability of Cameriere’s European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children.Moreover,the performance of dental age estimation based on Cameriere’s method combining the developmental information of permanent teeth(PT)and third molar(TM)was also analysed.Orthopantomographs of 720 healthy children in Group A,and orthopantomographs of 320 children and 280 subadults in Group B were assessed.The samples of Group A were divided into training dataset 1 and test dataset 1,and the samples of Group B were also divided into training dataset 2 and test dataset 2.A South China-specific formula was established based on the training dataset 1,and the comparison of accuracy between the Cameriere’s European formula and the South China-specific formula was conducted with the test dataset 1.Additionally,a PT regression model,a TM regression model,and a combined regression model(PTþTM)were established based on the training dataset 2,and the performance of these three models were validated on the test dataset 2.The Cameriere’s European formula underestimated chronological age with a mean difference(ME)of-0.47±1.11 years in males and-0.69±1.19 years in females.However,the South China-specific formula underestimated chronological age,with a mean difference(ME)of-0.02±0.71 years in males and-0.14±0.73 years in females.Compared with PT model and TM model,the PT and TM combined model obtained the smallest root mean square error(RMSE)of 1.29 years in males and 0.93 years in females.In conclusion,the South China-specific formula was more suitable for assessing the dental age of children in South China,and the PT and TM combined model can improve the accuracy of dental age estimation in children.展开更多
MicroRNAs(miRNAs)are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression.They are involved in the skin wound healing process with a dynamic expression patte...MicroRNAs(miRNAs)are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression.They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation.However,no reports have described any miRNAs as suitable reference genes(RGs)for miRNA quantification in wounded skin or samples with post-mortem changes.Here,we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation.Overall,nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals(PTls)were preselected by next-generation sequencing as candidate RGs.These nine miRNAs and the commonly used reference genes(comRGs:U6,GAPDH,ACTB,18S,5S,LC-Ogdh)were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTls during skin wound healing in mice.The stabilities of these genes were evaluated using four independent algorithms:GeNorm,NormFinder,BestKeeper,and comparative Delta Ct.Stability was further evaluated in mice with different post-mortem intervals(PMls).Overall,mmu-miR-26a-5p,mmu-miR-30d-5p,and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMls.These three miRNA RGs were additionally validated and compared with the comRGs in human samples.After assessing using one,two,or three miRNAs in combination for stability at different PTls,PMls,or in human samples,the set of miR-26a/30d/152 was approved as the best normalizer.In conclusion,our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation.展开更多
Wound age estimation is a crucial and challenging problem in forensic pathology.Although mRNA is the most commonly used indicator for wound age estimation,screening criteria are lacking.In the present study,the feasib...Wound age estimation is a crucial and challenging problem in forensic pathology.Although mRNA is the most commonly used indicator for wound age estimation,screening criteria are lacking.In the present study,the feasibility of screening criteria using mRNA to determine injury time based on the adenylate-uridylate-rich element(ARE)structure and gene ontology(GO)categories were evaluated.A total of 78 Sprague-Dawley male rats were contused and sampled at 4,8,12,16,20,24,28,32,36,40,44,and 48 h after inflicting injury.The candidate mRNAs were classified based on with or without ARE structure and GO category function.The mRNA expression levels were detected using qRT-PCR.In addition,the standard deviation(STD),mean deviation(MD),relative average deviation(d%),and coefficient of variation(CV)were calculated based on mRNA expression levels.The CV score(CVs)and the CV of CV(CV’CV)were calculated to measure heterogeneity.Finally,based on classic principles,the accuracy of combination of candidate mRNAs was assessed using discriminant analysis to construct a multivariate model for inferring wound age.The results of homogeneity evaluation of each group based on CVs were consistent with the MD,STD,d%,and CV results,indicating the credibility of the evaluation results based on CVs.The candidate mRNAs without ARE structure and classified as cellular component(CC)GO category(ARE-CC)had the highest CVs,showing the mRNAs with these characteristics are the most homogenous mRNAs and best suited for wound age estimation.The highest accuracy was 91.0%when the mRNAs without ARE structure were used to infer the wound age based on the discrimination model.The accuracy of mRNAs classified into CC or multiple function(MF)GO category was higher than mRNAs in the biological process(BP)category.In all subgroups,the accuracy of the composite identification model of mRNA composition without ARE structure and classified as CC was higher than other subgroups.The mRNAs without ARE structure and belonging to the CC GO category were more homogenous,showed higher accuracy for estimating wound age,and were appropriate for rat skeletal muscle wound age estimation.展开更多
Due to the secondary dentin formation,the dental pulp undergoes changes in shape throughout life.Based on this phenomenon,the Kvaal method has been applied to various populations for age estimation,and its usefulness ...Due to the secondary dentin formation,the dental pulp undergoes changes in shape throughout life.Based on this phenomenon,the Kvaal method has been applied to various populations for age estimation,and its usefulness has been verified.When applying the Kvaal method to Chinese subjects,we observed a relatively strong correlation between mandibular canines and age.This study notes the correlation between canines and chronological age and is the first to identify which canine is most closely related to chronological age.In addition,a new,simpler formula is determined based on canines according to Kvaal’s methodology.The radiographs of 360 individuals from northern China were selected,from which the widths and lengths of the pulp from four canines were measured according to the Kvaal method.Next,inter-and intra-observer reliabilities were analyzed in order to assess the repeatability of these measurements.The correlation between measurements and age was examined,and Chinese-specific age estimation formulae were derived.The results revealed that the ratios from the left maxillary canine exhibited the strongest correlation with age compared to the other canines,whereas the left mandibular canine showed the weakest correlation,which may contribute to the overall poor correlation of mandibular canines with age.What’s more,the formula derived from the left maxillary canine in this study displayed the highest coefficients of determination,and the formula derived from all canines showed the lowest residuals.Both of these formulae performed better than the Chinese-specific formula derived from six different types of teeth in our previous study,which had formerly possessed the highest coefficients of determination and the lowest residuals.Thus,we concluded that canines do play an important role in age estimation in the Chinese population,and the correlation between maxillary canines and chronological age is stronger than that of mandibular canines,although no distinct trend as to which side is better correlated with age was established.Going forward,we recommend the analysis of additional samples from different geographical regions and populations to further verify the importance of canines in age estimation.展开更多
Dental age estimation plays an important role in the field of clinic medicine and forensic medicine.The Demirjian and Nolla methods are common scoring methods for dental age estimation but there was no research about ...Dental age estimation plays an important role in the field of clinic medicine and forensic medicine.The Demirjian and Nolla methods are common scoring methods for dental age estimation but there was no research about the comparison of accuracy of these two methods in northeastern Chinese children.Hence,in this study,we compared the accuracy of these two methods to explore more suitable method for our studied population.We collected 535 orthopantomograms from northern Chinese children aged from 6 to 15 years and divided them into training dataset and testing dataset according to the ratio of 7:3.The dental age of training dataset were estimated using Demirjian and Nolla methods,respectively.The results suggested that the mean differences of these two methods were 0.24 and−0.40 years,and mean absolute difference were 0.65 and 0.59 years.Then to further improve the accuracy of dental age assessment,the new improved formulas and dental age conversion tables were established after analyzing the relationship between the sum scores based on Nolla method and chronology age in training dataset.According to the new method used in testing dataset,the minimum value of mean difference(0.00)and mean absolute difference(0.49)were obtained,which are largely smaller than that of Demirjian and Nolla methods.The new developed method and dental age conversion scales may be more suitable dental age estimation method for northeastern Chinese children.展开更多
Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences.Various statistical approaches have proposed by considering the teeth and mandible.However,building automated ...Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences.Various statistical approaches have proposed by considering the teeth and mandible.However,building automated dental age estimation based on machine learning techniques needs more research efforts.In this paper,an automated dental age estimation is proposed using transfer learning.In the proposed approach,features are extracted using two deep neural networks namely,AlexNet and ResNet.Several classifiers are proposed to perform the classification task including decision tree,k-nearest neighbor,linear discriminant,and support vector machine.The proposed approach is evaluated using a number of suitable performance metrics using a dataset that contains 1429 dental X-ray images.The obtained results show that the proposed approach has a promising performance.展开更多
As the use of facial attributes continues to expand,research into facial age estimation is also developing.Because face images are easily affected by factors including illumination and occlusion,the age estimation of ...As the use of facial attributes continues to expand,research into facial age estimation is also developing.Because face images are easily affected by factors including illumination and occlusion,the age estimation of faces is a challenging process.This paper proposes a face age estimation algorithm based on lightweight convolutional neural network in view of the complexity of the environment and the limitations of device computing ability.Improving face age estimation based on Soft Stagewise Regression Network(SSR-Net)and facial images,this paper employs the Center Symmetric Local Binary Pattern(CSLBP)method to obtain the feature image and then combines the face image and the feature image as network input data.Adding feature images to the convolutional neural network can improve the accuracy as well as increase the network model robustness.The experimental results on IMDB-WIKI and MORPH 2 datasets show that the lightweight convolutional neural network method proposed in this paper reduces model complexity and increases the accuracy of face age estimations.展开更多
Human age estimation from trace samples may give important leads early in a police investigation by contributing to the description of the perpetrator.Several molecular biomarkers are available for the estimation of c...Human age estimation from trace samples may give important leads early in a police investigation by contributing to the description of the perpetrator.Several molecular biomarkers are available for the estimation of chronological age,and currently,DNA methylation patterns are the most promising.In this study,a QIAGEN age protocol for age estimation was tested by five forensic genetic laboratories.The assay comprised bisulfite treatment of the extracted DNA,amplification of five CpG loci(in the genes of ELOVL2,C1orf132,TRIM59,KLF14,and FHL2),and sequencing of the amplicons using the PyroMark Q48 platform.Blood samples from 49 individuals with ages ranging from 18 to 64 years as well as negative and methylation controls were analyzed.An existing age estimation model was applied to display a mean absolute deviation of 3.62 years within the reference data set.展开更多
Dental development can be used to estimate age for forensic purposes.However,most of the currently available methods are less reliable for the Indonesian population due to population variability.This study presents a ...Dental development can be used to estimate age for forensic purposes.However,most of the currently available methods are less reliable for the Indonesian population due to population variability.This study presents a new method and evaluates other methods that utilize dental development to estimate the age of Indonesian people.Panoramic radiographs of 304 young Indonesian people aged 5–23 years old were analysed for deciduous tooth root resorption,permanent tooth calcification,and eruption.The extent of tooth root resorption was determined based on AlQahtani’s modified Moorrees et al.method.Tooth calcification was classified based on a modified Demirjian et al.method.Tooth eruption was evaluated based on AlQahtani’s modified Bengston system.The sequence of tooth root resorption,and permanent tooth calcification and eruption were grouped into 19 age categories(from 5–23 years old)in an atlas.The differences between males and females,between maxillary and mandibular teeth,and between right and left teeth were also analysed.There were minimal significant differences of tooth development between males and females,and between the right and left teeth(P>0.05),while the maxillary and mandibular dental development was significantly different(P<0.05).The newly developed atlas showed the development of the right side of maxillary and mandibular tooth of combined sex of Indonesian population.Another 34 panoramic radiographs of known-age and sex individuals from Indonesia were assessed using the newly developed Atlas of Dental Development in the Indonesian Population,Ubelaker’s Dental Development Chart,The London Atlas of Human Tooth Development and Eruption by AlQahtani,and the Age Estimation Guide-Modern Australia population by Blenkin-Taylor.Accuracy was assessed by comparing estimated age to actual chronological age using the Bland-Altmand test.Results show that the smallest range of error was found in the Atlas of Dental Development in the Indonesian Population(−0.969 to 1.210 years),followed by The London Atlas of Human Tooth Development and Eruption by AlQahtani(−2.013 to 1.990 years),the Age Estimation Guide-Modern Australia population by Blenkin-Taylor(−2.495 to 2.598 years),and the Dental Development Chart by Ubelaker(−2.960 to 3.289 years).These findings show that the Atlas of Dental Development constructed in this study performs better than the other three methods and presents greater accuracy of age estimation in the Indonesian population.展开更多
Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster cases.Traditionally,this process is done manually by human expert.However,the speed and accuracy ma...Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster cases.Traditionally,this process is done manually by human expert.However,the speed and accuracy may vary depending on the expertise level of the human expert and other human factors such as level of fatigue and attentiveness.To improve the recognition speed and consistency,researchers have proposed automated age estimation using deep learning techniques such as Convolutional Neural Network(CNN).CNN requires many training images to obtain high percentage of recognition accuracy.Unfortunately,it is very difficult to get large number of samples of dental images for training the CNN due to the need to comply to privacy acts.A promising solution to this problem is a technique called Generative Adversarial Network(GAN).GAN is a technique that can generate synthetic images that has similar statistics as the training set.A variation of GAN called Conditional GAN(CGAN)enables the generation of the synthetic images to be controlled more precisely such that only the specified type of images will be generated.This paper proposes a CGAN for generating new dental images to increase the number of images available for training a CNN model to perform age estimation.We also propose a pseudolabelling technique to label the generated images with proper age and gender.We used the combination of real and generated images to trainDentalAge and Sex Net(DASNET),which is a CNN model for dental age estimation.Based on the experiment conducted,the accuracy,coefficient of determination(R2)and Absolute Error(AE)of DASNET have improved to 87%,0.85 and 1.18 years respectively as opposed to 74%,0.72 and 3.45 years when DASNET is trained using real,but smaller number of images.展开更多
This is a correction to:Inês de Oliveira Santos,Isabel Poiares Baptista,Ricardo Henrique Alves da Silva,Eugénia Cunha,Evaluation of data collection bias of third molar stages of mineralisation for age estima...This is a correction to:Inês de Oliveira Santos,Isabel Poiares Baptista,Ricardo Henrique Alves da Silva,Eugénia Cunha,Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living,Forensic Sciences Research,Volume 9,Issue 2,June 2024,owae004,http://gffzzd3cc09b8251d45dfs905p9n9uvc5x6n9f.ffgz.tsg.suse.edu.cn/10.1093/fsr/owae004 The following changes have been made to the originally published article.展开更多
Objective: The objective of this study is to evaluate the accuracy of patient age estimation from frontal chest radiographs of adult patients. Methods: 195 posterior-anterior chest radiographs without significant abno...Objective: The objective of this study is to evaluate the accuracy of patient age estimation from frontal chest radiographs of adult patients. Methods: 195 posterior-anterior chest radiographs without significant abnormalities were shown to 5 staff radiologists and 6 radiology residents, who were asked to provide their estimates of patient age to the nearest decade. Real patient age distribution ranged from 16 to 91 years of age. Results: On average, correct estimate of patient age decade was made in 22% of cases. Staff radiologists were overall more accurate in their estimations compared to residents. Best accuracy was achieved by the radiologist with the most years of clinical experience, however overall accuracy did not tend to correlate with number of years in practice for staff, nor years of post-graduate training for residents. Overall, patient age was most often overestimated. The least accurate estimates were made for patients younger than 20 years and older than 90. Best accuracy was seen for patients between 50 and 70 years of age. For patients between 20 and 90 years of age, overall estimates were within 11 - 15 years of their true age. There was no significant difference in accuracy of age estimation between radiographs of women and men. Conclusions: Average rate of correct age estimation to the nearest decade from normal frontal chest radiographs in our study was 22%. Staff radiologists were more accurate than radiology residents. Best estimates were made for middle-aged patients, and worst for extremes of age.展开更多
For disaster victim identification(DVI),the destruction of human remains can pose significant challenges in discerning useful identifying details.In such cases,dental age estimation may help to identify individuals,bu...For disaster victim identification(DVI),the destruction of human remains can pose significant challenges in discerning useful identifying details.In such cases,dental age estimation may help to identify individuals,but tends to be less accurate for adults than for younger victims with less mature dentition.The Kvaal and Cameriere methods are used to estimate adult age by radiologically assessing pulp reduction resulting from the secondary dentin deposition in single-rooted teeth.This review aims to provide a meta-analysis of recent studies and their accuracy using Kvaal and Cameriere methods for adult age estimation from radiological pulp assessment.Searches were conducted in databases including Scielo,PubMed,EBSCO,Scopus,ScienceDirect,and Wiley Online Library.The searches were performed using the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA).The search resulted in 1241 studies of which 39 studies were eligible to be included.These studies comprised data from 12 distinct populations with a total of 7510 samples.The Kvaal method underestimated(−2.95 years,95%CI)and the Cameriere method overestimated(0.89 years,95%CI)the assessed adult age in this meta-analysis.The Cameriere method presented lower mean difference and standard error of the estimation(SEE)compared to the Kvaal method.Overall,both methods can be used as adjunctive methods to estimate adult age through population-specific equations.展开更多
Age estimation plays an important role in human-computer interaction system.The lack of large number of facial images with definite age label makes age estimation al-gorithms inefficient.Deep label distribution learni...Age estimation plays an important role in human-computer interaction system.The lack of large number of facial images with definite age label makes age estimation al-gorithms inefficient.Deep label distribution learning(DLDL)which employs convolutional neural networks(CNN)and label distribution learning to learn ambiguity from ground-truth age and adjacent ages,has been proven to outperform current state-of-the-art framework.However,DLDL assumes a rough label distribution which covers all ages for any given age label.In this paper,a more practical label distribution paradigm is proposed:we limit age label distribution that only covers a reasonable number of neighboring ages.In addition,we explore different label distributions to improve the performance of the proposed learning model.We employ CNN and the improved label distribution learning to estimate age.Experimental results show that compared to the DLDL,our method is more effective for facial age recognition.展开更多
Semen stain is one of the most important biological evidence at sexual crime scenes.Age estimation of human semen stains plays an important role in forensic work,and it is rarely studied due to lack of well-establishe...Semen stain is one of the most important biological evidence at sexual crime scenes.Age estimation of human semen stains plays an important role in forensic work,and it is rarely studied due to lack of well-established methods.In this study,the technique called attenuated total reflection Fourier transform infrared spectroscopy(ATR-FTIR)coupled with advanced chemometric methods was employed to determine the age of semen stains on three different substrates:glass slides,tissues and fabric made of regenerated cellulose fibres up to 6 d.Partial least squares regression(PLSR)was used in conjunction with spectral analysis for age estimation,and the results generated high R2 values(cross-validation:0.81,external validation:0.74)but a narrow margin of error for root mean square error(RMSE)(RMSE of cross-validation:0.77 d,RMSE of prediction:1.02 d).Additionally,our results indicated the robustness of PLSR model was not weaken by the influence of different substrates in this study.Our results indicate that ATR-FTIR,combined with chemometric methods,shows great potential as a convenient and efficient tool for age estimation of semen stains.Moreover,the method could be applied to routine forensic investigations in the future.展开更多
摘要Age at death is one of the key elements of the“biological profile"prepared when analysing unidentified human remains.Biological age is determined according to physiological indicators and developmental stage,which can be determined by bone assessment.It is worth remembering that the researcher must interpret each case individually and in accordance with the current state of knowledge.One of the most developed tools for analysing human remains is postmortem computed tomography.This allows for the visualization not only of bones without maceration but also of the entire body under various altered states,including corpses in advanced stages of decomposition and burnt bodies.The aim of this review is to present the current methods for age estimation based on postmortem computed tomography evaluation,comparing the results presented in 18 research projects published between 2013 and 2023 on foetuses,children,and adults from contemporary populations.Recent literature includes assessment of bones and characteristics such as skulls,teeth,vertebrae,pelvises,and long bones to estimate age at death.We cover the methods used in this recent literature,including machine learning,and discuss the advantages and disadvantages of them.
摘要This study evaluates the accuracy and reliability of the˙Iscan and Hartnett methods for estimating the age of adults based on rib analysis,using a sample of 127 pairs of ribs from a contemporary European population.The study employed a double-blind design with repeated measurements conducted by two observers.The˙Iscan method demonstrated a higher success rate,accurately assigning age in 62%of cases,compared to 38%for the Hartnett method.Both methods exhibited moderate intra-and interoperator agreement,as measured by Cohen’s Kappa.A detailed statistical analysis,including logistic regression,revealed significant discrepancies in phase-assignment accuracy between the two methods.The˙Iscan method’s success rate improved when prioritizing the highest observed phase,indicating potential for enhancing accuracy through strategic methodological adjustments.The findings underscore the importance of operator training and the need for consistent application of criteria.This research highlights the critical need for standardization in age estimation methods and suggests potential improvements for forensic and anthropological applications.The study contributes valuable insights into the strengths and limitations of widely used skeletal age estimation techniques,with implications for improving methodological consistency and accuracy in forensic investigations.
摘要Age estimation of adults is a challenging procedure in forensic practice.Inspired by the previous work by Chinese scholars,we established population-specific age estimation models from the osseous and calcified projections(OCPs)of costal cartilages,using three-dimensional volume-rendering technique.A total of 168 clinical CT scans(2 mm slice thickness)were used to develop the sex-specific age prediction models from a sample of Egyptians,comprising 70 females and 98 males,with documented ages between 12 and 85 years.The sample was also used for validating the Chinese model.We reported the differences between the predictive accuracy of the Egyptian(population specific)and Chinese(non-population specific)models.The most accurate age estimation model was stepwise linear regression with standard error of estimates of 10.9 and 11.8 years in males and females,respectively.For the simple linear regression models,the most accurate formula included OCP of the right second costal cartilage in males and OCP of the left third costal cartilage in females with standard error of estimates of 11.2 and 12.2 years,respectively,and mean absolute error(MAE)of 8.8 and 9.6 years,respectively.By comparison,the best accuracy rates produced by the Chinese vs.the Egyptian models in males and females within 5 years were 30.61%and 32.86%vs.35.71%and 32.86%,respectively,whereas within 10 years,the accuracy rates increased up to 57.14%and 58.57%vs.72.45%and 64.29%,respectively.Although the accuracy rates from the Chinese models were lower than those obtained from the Egyptian models,the MAE and least error values were comparable in both sexes.Notable accurate age estimation rates in the advanced age group≥40 years were reached being 81.25%to 97.92%in males and 69.77%to 93.02%in females.OCP of the right first costal cartilage was the most accurate in cross-population application for males and females with MAE values of 10.7 and 11.03 years,respectively,with balanced accuracy rates of age estimation using the 10-year interval and 40-year cutoff.
基金supported by the National Natural Science Foundation of China[number 81901924 and 81971795].
摘要Wound age estimation is one of the most challenging and indispensable issues for forensic pathologists.Although many methods based on physical findings and biochemical tests can be used to estimate wound age,an objective and reliable method for inferring the time interval after injury remains difficult.In the present study,endogenous metabolites of contused skeletal muscle were investigated to estimate the time interval after injury.Animal model of skeletal muscle injury was established using Sprague–Dawley rat,and the contused muscles were sampled at 4,8,12,16,20,24,28,32,36,40,44,and 48 h postcontusion(n=9).Then,the samples were analysed using ultraperformance liquid chromatography coupled with high-resolution mass spectrometry.A total of 43 differential metabolites in contused muscle were determined by metabolomics method.They were applied to construct a two-level tandem prediction model for wound age estimation based on multilayer perceptron algorithm.As a result,all muscle samples were eventually divided into the following subgroups:4,8,12,16–20,24–32,36–40,and 44–48 h.The tandem model exhibited a robust performance and achieved a prediction accuracy of 92.6%,which was much higher than that of the single model.In summary,the multilayer perceptron–multilayer perceptron tandem machine-learning model based on metabolomics data can be used as a novel strategy for wound age estimation in future forensic casework.
摘要Aiming at the problem of long time-consuming and low accuracy of existing age estimation approaches,a new age estimation method using Gabor feature fusion,and an improved atomic search algorithm for feature selection is proposed.Firstly,texture features of five scales and eight directions in the face region are extracted by Gabor wavelet transform.The statistical histogram is introduced to encode and fuse the directional index with the largest feature value on Gabor scales.Secondly,a new hybrid feature selection algorithm chaotic improved atom search optimisation with simulated annealing(CIASO-SA)is presented,which is based on an improved atomic search algorithm and the simulated annealing algorithm.Besides,the CIASO-SA algorithm introduces a chaos mechanism during atomic initialisation,significantly improving the convergence speed and accuracy of the algorithm.Finally,a support vector machine(SVM)is used to get classification results of the age group.To verify the performance of the proposed algorithm,face images with three resolutions in the Adience dataset are tested.Using the Gabor real part fusion feature at 48�48 resolution,the average accuracy and 1-off accuracy of age classification exhibit a maximum of 60.4%and 85.9%,respectively.Obtained results prove the superiority of the proposed algorithm over the state-of-the-art methods,which is of great referential value for application to the mobile terminals.
基金National Natural Science Foundation of ChinaShanghai Key Laboratory of Forensic Medicine Open ProjectNatural Science Foundation of Hunan Province,China.
摘要The aim of this study was to evaluate the applicability of Cameriere’s European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children.Moreover,the performance of dental age estimation based on Cameriere’s method combining the developmental information of permanent teeth(PT)and third molar(TM)was also analysed.Orthopantomographs of 720 healthy children in Group A,and orthopantomographs of 320 children and 280 subadults in Group B were assessed.The samples of Group A were divided into training dataset 1 and test dataset 1,and the samples of Group B were also divided into training dataset 2 and test dataset 2.A South China-specific formula was established based on the training dataset 1,and the comparison of accuracy between the Cameriere’s European formula and the South China-specific formula was conducted with the test dataset 1.Additionally,a PT regression model,a TM regression model,and a combined regression model(PTþTM)were established based on the training dataset 2,and the performance of these three models were validated on the test dataset 2.The Cameriere’s European formula underestimated chronological age with a mean difference(ME)of-0.47±1.11 years in males and-0.69±1.19 years in females.However,the South China-specific formula underestimated chronological age,with a mean difference(ME)of-0.02±0.71 years in males and-0.14±0.73 years in females.Compared with PT model and TM model,the PT and TM combined model obtained the smallest root mean square error(RMSE)of 1.29 years in males and 0.93 years in females.In conclusion,the South China-specific formula was more suitable for assessing the dental age of children in South China,and the PT and TM combined model can improve the accuracy of dental age estimation in children.
基金supported by the National Natural Science Foundation of China[grant numbers 81871529,81971793,81801874]National Key Research and Development Program of China[grant number 2018YFC0807204]Liaoning Natural Science Foundation[grant number 20180550722].
摘要MicroRNAs(miRNAs)are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression.They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation.However,no reports have described any miRNAs as suitable reference genes(RGs)for miRNA quantification in wounded skin or samples with post-mortem changes.Here,we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation.Overall,nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals(PTls)were preselected by next-generation sequencing as candidate RGs.These nine miRNAs and the commonly used reference genes(comRGs:U6,GAPDH,ACTB,18S,5S,LC-Ogdh)were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTls during skin wound healing in mice.The stabilities of these genes were evaluated using four independent algorithms:GeNorm,NormFinder,BestKeeper,and comparative Delta Ct.Stability was further evaluated in mice with different post-mortem intervals(PMls).Overall,mmu-miR-26a-5p,mmu-miR-30d-5p,and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMls.These three miRNA RGs were additionally validated and compared with the comRGs in human samples.After assessing using one,two,or three miRNAs in combination for stability at different PTls,PMls,or in human samples,the set of miR-26a/30d/152 was approved as the best normalizer.In conclusion,our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation.
基金This study was supported by the Natural Science Foundation for Excellent Young Scientists of Shanxi Province(grant number 20191D211351)the National Natural Science Foundation of China(grant number 81971795 and 81601646).
摘要Wound age estimation is a crucial and challenging problem in forensic pathology.Although mRNA is the most commonly used indicator for wound age estimation,screening criteria are lacking.In the present study,the feasibility of screening criteria using mRNA to determine injury time based on the adenylate-uridylate-rich element(ARE)structure and gene ontology(GO)categories were evaluated.A total of 78 Sprague-Dawley male rats were contused and sampled at 4,8,12,16,20,24,28,32,36,40,44,and 48 h after inflicting injury.The candidate mRNAs were classified based on with or without ARE structure and GO category function.The mRNA expression levels were detected using qRT-PCR.In addition,the standard deviation(STD),mean deviation(MD),relative average deviation(d%),and coefficient of variation(CV)were calculated based on mRNA expression levels.The CV score(CVs)and the CV of CV(CV’CV)were calculated to measure heterogeneity.Finally,based on classic principles,the accuracy of combination of candidate mRNAs was assessed using discriminant analysis to construct a multivariate model for inferring wound age.The results of homogeneity evaluation of each group based on CVs were consistent with the MD,STD,d%,and CV results,indicating the credibility of the evaluation results based on CVs.The candidate mRNAs without ARE structure and classified as cellular component(CC)GO category(ARE-CC)had the highest CVs,showing the mRNAs with these characteristics are the most homogenous mRNAs and best suited for wound age estimation.The highest accuracy was 91.0%when the mRNAs without ARE structure were used to infer the wound age based on the discrimination model.The accuracy of mRNAs classified into CC or multiple function(MF)GO category was higher than mRNAs in the biological process(BP)category.In all subgroups,the accuracy of the composite identification model of mRNA composition without ARE structure and classified as CC was higher than other subgroups.The mRNAs without ARE structure and belonging to the CC GO category were more homogenous,showed higher accuracy for estimating wound age,and were appropriate for rat skeletal muscle wound age estimation.
基金supported by the National Natural Science Foundation of China[grant number 81701869]the China Postdoctoral Science Foundation[grant number 2019M653664]the Fundamental Research Funds for the Central Universities[grant number xjj2017168].
摘要Due to the secondary dentin formation,the dental pulp undergoes changes in shape throughout life.Based on this phenomenon,the Kvaal method has been applied to various populations for age estimation,and its usefulness has been verified.When applying the Kvaal method to Chinese subjects,we observed a relatively strong correlation between mandibular canines and age.This study notes the correlation between canines and chronological age and is the first to identify which canine is most closely related to chronological age.In addition,a new,simpler formula is determined based on canines according to Kvaal’s methodology.The radiographs of 360 individuals from northern China were selected,from which the widths and lengths of the pulp from four canines were measured according to the Kvaal method.Next,inter-and intra-observer reliabilities were analyzed in order to assess the repeatability of these measurements.The correlation between measurements and age was examined,and Chinese-specific age estimation formulae were derived.The results revealed that the ratios from the left maxillary canine exhibited the strongest correlation with age compared to the other canines,whereas the left mandibular canine showed the weakest correlation,which may contribute to the overall poor correlation of mandibular canines with age.What’s more,the formula derived from the left maxillary canine in this study displayed the highest coefficients of determination,and the formula derived from all canines showed the lowest residuals.Both of these formulae performed better than the Chinese-specific formula derived from six different types of teeth in our previous study,which had formerly possessed the highest coefficients of determination and the lowest residuals.Thus,we concluded that canines do play an important role in age estimation in the Chinese population,and the correlation between maxillary canines and chronological age is stronger than that of mandibular canines,although no distinct trend as to which side is better correlated with age was established.Going forward,we recommend the analysis of additional samples from different geographical regions and populations to further verify the importance of canines in age estimation.
基金This project was supported by the National Natural Science Foundation of China[grant number 81871533 and 82002005]Natural Science Foundation of Hunan Province[grant number 2020JJ4779 and 2020JJ5787].
摘要Dental age estimation plays an important role in the field of clinic medicine and forensic medicine.The Demirjian and Nolla methods are common scoring methods for dental age estimation but there was no research about the comparison of accuracy of these two methods in northeastern Chinese children.Hence,in this study,we compared the accuracy of these two methods to explore more suitable method for our studied population.We collected 535 orthopantomograms from northern Chinese children aged from 6 to 15 years and divided them into training dataset and testing dataset according to the ratio of 7:3.The dental age of training dataset were estimated using Demirjian and Nolla methods,respectively.The results suggested that the mean differences of these two methods were 0.24 and−0.40 years,and mean absolute difference were 0.65 and 0.59 years.Then to further improve the accuracy of dental age assessment,the new improved formulas and dental age conversion tables were established after analyzing the relationship between the sum scores based on Nolla method and chronology age in training dataset.According to the new method used in testing dataset,the minimum value of mean difference(0.00)and mean absolute difference(0.49)were obtained,which are largely smaller than that of Demirjian and Nolla methods.The new developed method and dental age conversion scales may be more suitable dental age estimation method for northeastern Chinese children.
摘要Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences.Various statistical approaches have proposed by considering the teeth and mandible.However,building automated dental age estimation based on machine learning techniques needs more research efforts.In this paper,an automated dental age estimation is proposed using transfer learning.In the proposed approach,features are extracted using two deep neural networks namely,AlexNet and ResNet.Several classifiers are proposed to perform the classification task including decision tree,k-nearest neighbor,linear discriminant,and support vector machine.The proposed approach is evaluated using a number of suitable performance metrics using a dataset that contains 1429 dental X-ray images.The obtained results show that the proposed approach has a promising performance.
基金This work was funded by the foundation of Liaoning Educational committee under the Grant No.2019LNJC03.
摘要As the use of facial attributes continues to expand,research into facial age estimation is also developing.Because face images are easily affected by factors including illumination and occlusion,the age estimation of faces is a challenging process.This paper proposes a face age estimation algorithm based on lightweight convolutional neural network in view of the complexity of the environment and the limitations of device computing ability.Improving face age estimation based on Soft Stagewise Regression Network(SSR-Net)and facial images,this paper employs the Center Symmetric Local Binary Pattern(CSLBP)method to obtain the feature image and then combines the face image and the feature image as network input data.Adding feature images to the convolutional neural network can improve the accuracy as well as increase the network model robustness.The experimental results on IMDB-WIKI and MORPH 2 datasets show that the lightweight convolutional neural network method proposed in this paper reduces model complexity and increases the accuracy of face age estimations.
基金supported by LM2018125 for the work per-formed in Palacky University,Czech Republicby the National Institute of Justice,Department of Justice,USA under grant 2017-NE-BX-0001 for work performed at the Department of Chemistry and Biochemistry,Florida International University,Miami,FL,USA。
摘要Human age estimation from trace samples may give important leads early in a police investigation by contributing to the description of the perpetrator.Several molecular biomarkers are available for the estimation of chronological age,and currently,DNA methylation patterns are the most promising.In this study,a QIAGEN age protocol for age estimation was tested by five forensic genetic laboratories.The assay comprised bisulfite treatment of the extracted DNA,amplification of five CpG loci(in the genes of ELOVL2,C1orf132,TRIM59,KLF14,and FHL2),and sequencing of the amplicons using the PyroMark Q48 platform.Blood samples from 49 individuals with ages ranging from 18 to 64 years as well as negative and methylation controls were analyzed.An existing age estimation model was applied to display a mean absolute deviation of 3.62 years within the reference data set.
摘要Dental development can be used to estimate age for forensic purposes.However,most of the currently available methods are less reliable for the Indonesian population due to population variability.This study presents a new method and evaluates other methods that utilize dental development to estimate the age of Indonesian people.Panoramic radiographs of 304 young Indonesian people aged 5–23 years old were analysed for deciduous tooth root resorption,permanent tooth calcification,and eruption.The extent of tooth root resorption was determined based on AlQahtani’s modified Moorrees et al.method.Tooth calcification was classified based on a modified Demirjian et al.method.Tooth eruption was evaluated based on AlQahtani’s modified Bengston system.The sequence of tooth root resorption,and permanent tooth calcification and eruption were grouped into 19 age categories(from 5–23 years old)in an atlas.The differences between males and females,between maxillary and mandibular teeth,and between right and left teeth were also analysed.There were minimal significant differences of tooth development between males and females,and between the right and left teeth(P>0.05),while the maxillary and mandibular dental development was significantly different(P<0.05).The newly developed atlas showed the development of the right side of maxillary and mandibular tooth of combined sex of Indonesian population.Another 34 panoramic radiographs of known-age and sex individuals from Indonesia were assessed using the newly developed Atlas of Dental Development in the Indonesian Population,Ubelaker’s Dental Development Chart,The London Atlas of Human Tooth Development and Eruption by AlQahtani,and the Age Estimation Guide-Modern Australia population by Blenkin-Taylor.Accuracy was assessed by comparing estimated age to actual chronological age using the Bland-Altmand test.Results show that the smallest range of error was found in the Atlas of Dental Development in the Indonesian Population(−0.969 to 1.210 years),followed by The London Atlas of Human Tooth Development and Eruption by AlQahtani(−2.013 to 1.990 years),the Age Estimation Guide-Modern Australia population by Blenkin-Taylor(−2.495 to 2.598 years),and the Dental Development Chart by Ubelaker(−2.960 to 3.289 years).These findings show that the Atlas of Dental Development constructed in this study performs better than the other three methods and presents greater accuracy of age estimation in the Indonesian population.
摘要Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster cases.Traditionally,this process is done manually by human expert.However,the speed and accuracy may vary depending on the expertise level of the human expert and other human factors such as level of fatigue and attentiveness.To improve the recognition speed and consistency,researchers have proposed automated age estimation using deep learning techniques such as Convolutional Neural Network(CNN).CNN requires many training images to obtain high percentage of recognition accuracy.Unfortunately,it is very difficult to get large number of samples of dental images for training the CNN due to the need to comply to privacy acts.A promising solution to this problem is a technique called Generative Adversarial Network(GAN).GAN is a technique that can generate synthetic images that has similar statistics as the training set.A variation of GAN called Conditional GAN(CGAN)enables the generation of the synthetic images to be controlled more precisely such that only the specified type of images will be generated.This paper proposes a CGAN for generating new dental images to increase the number of images available for training a CNN model to perform age estimation.We also propose a pseudolabelling technique to label the generated images with proper age and gender.We used the combination of real and generated images to trainDentalAge and Sex Net(DASNET),which is a CNN model for dental age estimation.Based on the experiment conducted,the accuracy,coefficient of determination(R2)and Absolute Error(AE)of DASNET have improved to 87%,0.85 and 1.18 years respectively as opposed to 74%,0.72 and 3.45 years when DASNET is trained using real,but smaller number of images.
摘要This is a correction to:Inês de Oliveira Santos,Isabel Poiares Baptista,Ricardo Henrique Alves da Silva,Eugénia Cunha,Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living,Forensic Sciences Research,Volume 9,Issue 2,June 2024,owae004,http://gffzzd3cc09b8251d45dfs905p9n9uvc5x6n9f.ffgz.tsg.suse.edu.cn/10.1093/fsr/owae004 The following changes have been made to the originally published article.
摘要Objective: The objective of this study is to evaluate the accuracy of patient age estimation from frontal chest radiographs of adult patients. Methods: 195 posterior-anterior chest radiographs without significant abnormalities were shown to 5 staff radiologists and 6 radiology residents, who were asked to provide their estimates of patient age to the nearest decade. Real patient age distribution ranged from 16 to 91 years of age. Results: On average, correct estimate of patient age decade was made in 22% of cases. Staff radiologists were overall more accurate in their estimations compared to residents. Best accuracy was achieved by the radiologist with the most years of clinical experience, however overall accuracy did not tend to correlate with number of years in practice for staff, nor years of post-graduate training for residents. Overall, patient age was most often overestimated. The least accurate estimates were made for patients younger than 20 years and older than 90. Best accuracy was seen for patients between 50 and 70 years of age. For patients between 20 and 90 years of age, overall estimates were within 11 - 15 years of their true age. There was no significant difference in accuracy of age estimation between radiographs of women and men. Conclusions: Average rate of correct age estimation to the nearest decade from normal frontal chest radiographs in our study was 22%. Staff radiologists were more accurate than radiology residents. Best estimates were made for middle-aged patients, and worst for extremes of age.
摘要For disaster victim identification(DVI),the destruction of human remains can pose significant challenges in discerning useful identifying details.In such cases,dental age estimation may help to identify individuals,but tends to be less accurate for adults than for younger victims with less mature dentition.The Kvaal and Cameriere methods are used to estimate adult age by radiologically assessing pulp reduction resulting from the secondary dentin deposition in single-rooted teeth.This review aims to provide a meta-analysis of recent studies and their accuracy using Kvaal and Cameriere methods for adult age estimation from radiological pulp assessment.Searches were conducted in databases including Scielo,PubMed,EBSCO,Scopus,ScienceDirect,and Wiley Online Library.The searches were performed using the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA).The search resulted in 1241 studies of which 39 studies were eligible to be included.These studies comprised data from 12 distinct populations with a total of 7510 samples.The Kvaal method underestimated(−2.95 years,95%CI)and the Cameriere method overestimated(0.89 years,95%CI)the assessed adult age in this meta-analysis.The Cameriere method presented lower mean difference and standard error of the estimation(SEE)compared to the Kvaal method.Overall,both methods can be used as adjunctive methods to estimate adult age through population-specific equations.
基金the financial support of the China National Natural Science Foundation(61702095)Natural Science Founda-tion(njpj2018209)of Nanjing Tech University Pujiang Institute,Anhui Polytechnic University Scientific Research Foundation(S031702004)+1 种基金Natural Science Foundation of Fujian Province(2018J01806)Scientific Research Pro-gram of Outstanding Talents in Universities of Fujian。
摘要Age estimation plays an important role in human-computer interaction system.The lack of large number of facial images with definite age label makes age estimation al-gorithms inefficient.Deep label distribution learning(DLDL)which employs convolutional neural networks(CNN)and label distribution learning to learn ambiguity from ground-truth age and adjacent ages,has been proven to outperform current state-of-the-art framework.However,DLDL assumes a rough label distribution which covers all ages for any given age label.In this paper,a more practical label distribution paradigm is proposed:we limit age label distribution that only covers a reasonable number of neighboring ages.In addition,we explore different label distributions to improve the performance of the proposed learning model.We employ CNN and the improved label distribution learning to estimate age.Experimental results show that compared to the DLDL,our method is more effective for facial age recognition.
基金This work was supported by the National Natural Science Foundation of China[grant number 81730056].
摘要Semen stain is one of the most important biological evidence at sexual crime scenes.Age estimation of human semen stains plays an important role in forensic work,and it is rarely studied due to lack of well-established methods.In this study,the technique called attenuated total reflection Fourier transform infrared spectroscopy(ATR-FTIR)coupled with advanced chemometric methods was employed to determine the age of semen stains on three different substrates:glass slides,tissues and fabric made of regenerated cellulose fibres up to 6 d.Partial least squares regression(PLSR)was used in conjunction with spectral analysis for age estimation,and the results generated high R2 values(cross-validation:0.81,external validation:0.74)but a narrow margin of error for root mean square error(RMSE)(RMSE of cross-validation:0.77 d,RMSE of prediction:1.02 d).Additionally,our results indicated the robustness of PLSR model was not weaken by the influence of different substrates in this study.Our results indicate that ATR-FTIR,combined with chemometric methods,shows great potential as a convenient and efficient tool for age estimation of semen stains.Moreover,the method could be applied to routine forensic investigations in the future.