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Sequential Similarity Detection Algorithm Based on Image Edge Feature 认领 引用 被引量：5
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作者 马国红 王聪 +1 位作者 刘沛 朱书林 《Journal of Shanghai Jiaotong university(Science)》 EI 2014年第1期79-83,共5页
： This paper proposes a new sequential similarity detection algorithm （SSDA）, which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorith... ： This paper proposes a new sequential similarity detection algorithm （SSDA）, which can overcome matching error caused by grayscale distortion; meanwhile, time consumption is much less than that of regular algorithms based on image feature. The algorithm adopts Sobel operator to deal with subgraph and template image, and regards the region which has maximum relevance as final result. In order to solve time-consuming problem existing in original algorithm, a coarse-to-fine matching method is put forward. Besides, the location correlation keeps updating and remains the minimum value in the whole scanning process, which can significantly decrease time consumption. Experiments show that the algorithm proposed in this article can not only overcome gray distortion, but also ensure accuracy. Time consumption is at least one time orders of magnitude shorter than that of primal algorithm. 展开更多
关键词 welding image feature matching sequential similarity detection algorithm(SSDA) self-adaption value
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Improvement of High-Speed Detection Algorithm for Nonwoven Material Defects Based on Machine Vision 认领 引用 被引量：3
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作者 LI Chengzu WEI Kehan +4 位作者 ZHAO Yingbo TIAN Xuehui QIAN Yang ZHANG Lu WANG Rongwu 《Journal of Donghua University(English Edition)》 CAS 2024年第4期416-427,共12页
Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,maki... Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production. 展开更多
关键词 defect detection nonwoven materials deep learning object detection algorithm transfer learning halfprecision quantization
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A fast detection algorithm for ceramic ball surface defects based on fringe reflection 认领 引用 被引量：4
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作者 SUN Ying FU Lu-hua WANG Zhong 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2020年第1期28-37,共10页
A ceramic ball is a basic part widely used in precision bearings.There is no perfect testing equipment for ceramic ball surface defects at present.A fast visual detection algorithm for ceramic ball surface defects bas... A ceramic ball is a basic part widely used in precision bearings.There is no perfect testing equipment for ceramic ball surface defects at present.A fast visual detection algorithm for ceramic ball surface defects based on fringe reflection is designed.By means of image preprocessing,grayscale value accumulative differential positioning,edge detection,pixel-value row difference and template matching,the algorithm can locate feature points and judge whether the spherical surface has defects by the number of points.Taking black silicon nitride ceramic balls with a diameter of 6.35 mm as an example,the defect detection time for a single gray scale image is 0.78 s,and the detection limit is 16.5μm. 展开更多
关键词 ceramic ball surface defect fringe reflection visual detection algorithm
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Signal Detection Algorithm Design Based on Stochastic Resonance Technology Under Low Signal-to-Noise Ratio 认领 引用 被引量：1
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作者 JIANG Xiaolin DIAO Ming QU Susu 《Journal of Shanghai Jiaotong university(Science)》 EI 2019年第3期328-334,共7页
In the current 4th generation(4G)communication network,the base station with the same frequency transmission makes a serious interference among adjacent cells,and information transmission is susceptible to interferenc... In the current 4th generation(4G)communication network,the base station with the same frequency transmission makes a serious interference among adjacent cells,and information transmission is susceptible to interference such as channel multipath fading and occlusion effect.Detecting effectively spectrum signal under low signal-to-noise ratio(SNR),directly affects the whole performance of the wireless communication network system.This paper designs an energy signal detection algorithm based on stochastic resonance technology which transforms noise's signal energy into useful signal energy,and improves output SNR.The energy signal detection algorithm realizes the function of providing effective detection of signal under low SNR,and promotes the performance of the whole communication system. 展开更多
关键词 4G communication network stochastic resonance signal detection algorithm
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A Parameter-Detection Algorithm for Moving Ships 认领 引用
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作者 Yaduan Ruan Juan Liao +2 位作者 Jiang Wang Bo Li Qimei Chen 《ZTE Communications》 2015年第2期23-27,共5页
In traffic-monitoring systems,numerous vision-based approaches have been used to detect vehicle parameters.However,few of these approaches have been used in waterway transport because of the complexity created by fact... In traffic-monitoring systems,numerous vision-based approaches have been used to detect vehicle parameters.However,few of these approaches have been used in waterway transport because of the complexity created by factors such as rippling water and lack of calibration object.In this paper,we present an approach to detecting the parameters of a moving ship in an inland river.This approach involves interactive calibration without a calibration reference.We detect a moving ship using an optimized visual foreground detection algorithm that eliminates false detection in dynamic water scenarios,and we detect ship length,width,speed,and flow.We trialed our parameter-detection technique in the Beijing-Hangzhou Grand Canal and found that detection accuracy was greater than 90%for all parameters. 展开更多
关键词 video analysisl interactive calibration foreground detection algorithm traffic parameter delection
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Density-based trajectory outlier detection algorithm 认领 引用 被引量：13
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作者 Zhipeng Liu Dechang Pi Jinfeng Jiang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第2期335-340,共6页
With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the pr... With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the problem of anomaly detection is a hot topic.Based on the development of anomalous trajectory detection of moving objects,this paper introduces the classical trajectory outlier detection（TRAOD） algorithm,and then proposes a density-based trajectory outlier detection（DBTOD） algorithm,which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense.The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented,which show the effectiveness of the algorithm. 展开更多
关键词 density-based algorithm trajectory outlier detection（TRAOD） partition-and-detect framework Hausdorff distance
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Steel Surface Defect Detection via the Multiscale Edge Enhancement Method 认领 引用 被引量：1
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作者 Yuanyuan Wang Yemeng Zhu +2 位作者 Xiuchuan Chen Tongtong Yin Shiwei Su 《Computers, Materials & Continua》 SCIE EI 2026年第3期1006-1032,共27页
To solve the false detection and missed detection problems caused by various types and sizes of defects in the detection of steel surface defects,similar defects and background features,and similarities between differ... To solve the false detection and missed detection problems caused by various types and sizes of defects in the detection of steel surface defects,similar defects and background features,and similarities between different defects,this paper proposes a lightweight detection model named multiscale edge and squeeze-and-excitation attention detection network(MSESE),which is built upon the You Only Look Once version 11 nano(YOLOv11n).To address the difficulty of locating defect edges,we first propose an edge enhancement module(EEM),apply it to the process of multiscale feature extraction,and then propose a multiscale edge enhancement module(MSEEM).By obtaining defect features from different scales and enhancing their edge contours,the module uses the dual-domain selection mechanism to effectively focus on the important areas in the image to ensure that the feature images have richer information and clearer contour features.By fusing the squeeze-and-excitation attention mechanism with the EEM,we obtain a lighter module that can enhance the representation of edge features,which is named the edge enhancement module with squeeze-and-excitation attention(EEMSE).This module was subsequently integrated into the detection head.The enhanced detection head achieves improved edge feature enhancement with reduced computational overhead,while effectively adjusting channel-wise importance and further refining feature representation.Experiments on the NEU-DET dataset show that,compared with the original YOLOv11n,the improved model achieves improvements of 4.1%and 2.2%in terms of mAP@0.5 and mAP@0.5:0.95,respectively,and the GFLOPs value decreases from the original value of 6.4 to 6.2.Furthermore,when compared to current mainstream models,Mamba-YOLOT and RTDETR-R34,our method achieves superior performance with 6.5%and 8.9%higher mAP@0.5,respectively,while maintaining a more compact parameter footprint.These results collectively validate the effectiveness and efficiency of our proposed approach. 展开更多
关键词 Steel defects object detection algorithms small target multiscale attention mechanism
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Damage Detection of X-ray Image of Conveyor Belts with Steel Rope Cores Based on Improved FCOS Algorithm 认领 引用 被引量：1
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作者 WANG Baomin DING Hewei +1 位作者 TENG Fei LIU Hongqin 《Journal of Shanghai Jiaotong university(Science)》 EI 2025年第2期309-318,共10页
Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is propose... Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is proposed based on the improved fully convolutional one-stage object detection(FCOS)algorithm.The regression performance of bounding boxes was optimized by introducing the complete intersection over union loss function into the improved algorithm.The feature fusion network structure is modified by adding adaptive fusion paths to the feature fusion network structure,which makes full use of the features of accurate localization and semantics of multi-scale feature fusion networks.Finally,the network structure was trained and validated by using the X-ray image dataset of damages in conveyor belts with steel rope cores provided by a flaw detection equipment manufacturer.In addition,the data enhancement methods such as rotating,mirroring,and scaling,were employed to enrich the image dataset so that the model is adequately trained.Experimental results showed that the improved FCOS algorithm promoted the precision rate and the recall rate by 20.9%and 14.8%respectively,compared with the original algorithm.Meanwhile,compared with Fast R-CNN,Faster R-CNN,SSD,and YOLOv3,the improved FCOS algorithm has obvious advantages;detection precision rate and recall rate of the modified network reached 95.8%and 97.0%respectively.Furthermore,it demonstrated a higher detection accuracy without affecting the speed.The results of this work have some reference significance for the automatic identification and detection of steel core conveyor belt damage. 展开更多
关键词 conveyer belts with steel rope cores damage X-ray image image detection improved fully convo-lutional one-stage object detection(FCOS)algorithm
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Automatic Recognition Algorithm of Pavement Defects Based on S3M and SDI Modules Using UAV-Collected Road Images 认领 引用
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作者 Hongcheng Zhao Tong Yang +1 位作者 Yihui Hu Fengxiang Guo 《Structural Durability & Health Monitoring》 EI 2026年第1期121-137,共17页
With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-... With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning. 展开更多
关键词 Pavement defects state space model UAV detection algorithm image processing
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An edge detection algorithm for imaging ladar 认领 引用 被引量：11
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作者 王骐 李自勤 +2 位作者 李琦 孙剑峰 傅俊诚 《Chinese Optics Letters》 EI CAS 2003年第5期272-274,共3页
In this paper, the morphological filter based on parametric edge detection is presented and applied to imaging ladar image with speckle noise. This algorithm and Laplacian of Gaussian (LOG) operator are compared on ed... In this paper, the morphological filter based on parametric edge detection is presented and applied to imaging ladar image with speckle noise. This algorithm and Laplacian of Gaussian (LOG) operator are compared on edge detection. The experimental results indicate the superior performance of this kind of the edge detection. 展开更多
关键词 for on de it et An edge detection algorithm for imaging ladar of Figure test LOG from than that HO in be
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Shadow regions detection algorithm by adaptive narrowband two-phase Chan-Vese model 认领 引用 被引量：2
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作者 WANG Xingmei YIN Guisheng +2 位作者 LIU Guangyu LIU Zhipeng WANG Xiaowei 《Chinese Journal of Acoustics》 CSCD 2016年第3期292-308,共17页
An adaptive narrowband two-phase Chan-Vese （ANBCV） model is proposed for improving the shadow regions detection performance of sonar images. In the first noise smoothing step, the anisotropic second-order neighborho... An adaptive narrowband two-phase Chan-Vese （ANBCV） model is proposed for improving the shadow regions detection performance of sonar images. In the first noise smoothing step, the anisotropic second-order neighborhood MRF （Markov Random Field, MRF） is used to describe the image texture feature parameters. Then, initial two-class segmentation is processed with the block mode k-means clustering algorithm, to estimate the approximate position of the shadow regions. On this basis, the zero level set function is adaptively initialized by the approximate position of shadow regions. ANBCV model is provided to complete local optimization for eliminating the image global interference and obtaining more accurate results. Experimental results show that the new algorithm can efficiently remove partial noise, increase detection speed and accuracy, and with less human intervention. 展开更多
关键词 MRF Shadow regions detection algorithm by adaptive narrowband two-phase Chan-Vese model
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An echo detection algorithm for underwater continuous wave active detection 认领 引用 被引量：2
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作者 LIU Dali LIU Yuntao CAI Huizhi 《Chinese Journal of Acoustics》 2014年第1期22-31,共10页
The model of linear frequency modulation continuous wave （LFMCW） applied in underwater detection and the method for the detection of echo signal and the estimation of target parameters were studied. By analyzing the... The model of linear frequency modulation continuous wave （LFMCW） applied in underwater detection and the method for the detection of echo signal and the estimation of target parameters were studied. By analyzing the heterodyne signal, an algorithm with the structure of heterodyne-Practional Fourier Transform （FRFT） was proposed. To reduce the computation of searching targets in a two-dimensional FRFT result, the heterodyne signal would be processed by FRFT at a specific order, after Radon-Ambiguity Transform （RAT） was applied to estimate the sweep rate of the signal. Simulations proved that the algorithm can eliminate the coupling phenomenon of distance and velocity of LFMCW, and estimate targets＇ parameters accurately. The lake trial results showed that the processing gain of LFMCW processed by the algorithm in this paper was 13 dB better than that of the LFM processed by matched filter. The research results indicated that the algorithm applied in LFMCW underwater detection was feasible and effective, and it could estimate targets＇ parameters accurately and obtain a good detection performance. 展开更多
关键词 LFMCW FRFT An echo detection algorithm for underwater continuous wave active detection wave
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Broadband wireless access and IP technologies-VBLAST detection algorithm 认领 引用
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作者 Yiqing Wang 《Advances in Engineering Innovation》 2023年第1期1-10,共10页
MIMO technology was proposed as early as 1908 to cope with wireless channel fading.In 1995,Bell Labs was the first to discover the great potential of MIMO system in channel capacity,and in 1996,Foshini of Bell Labs fi... MIMO technology was proposed as early as 1908 to cope with wireless channel fading.In 1995,Bell Labs was the first to discover the great potential of MIMO system in channel capacity,and in 1996,Foshini of Bell Labs first proposed a space-time coding scheme,i.e.,the diagonal-Bell Labs hierarchical space-time model,which can obtain very high spectrum utilization,but due to the complexity of its structure,it is difficult to be applied in practice,and is now rarely investigated.1998,P.W.Wolniansky et al.gave a simple and practical space-time coding scheme on this basis,i.e.,the vertical-Bell Labs layered space-time model.In 1998,P.W.Wolniansky et al.gave a simple and practical space-time coding scheme on this basis,i.e.,Vertical Bell Labs Layered Space-Time(V-BLAST,Vertical Bell Labs Layered Space-Time)model,which can obtain very high spectrum utilisation and is easy to implement,and therefore has received wide attention once it was proposed.In this paper,we focus on airtime layered codes as well as the ZF detection algorithm and the MMSE detection algorithm in VBLAST systems and improve them to further enhance the performance of the two detection algorithms through sequential serial interference cancellation. 展开更多
关键词 MIMO multi-antenna VBLAST MMSE detection algorithm
A review of deep learning-based analyses of impact crater detection on different celestial bodies 认领 引用
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作者 Xu Zhang Jialong Lai +2 位作者 Feifei Cui Chunyu Ding Zhicheng Zhong 《Astronomical Techniques and Instruments》 CSCD 2025年第3期127-147,共21页
Planetary surfaces,shaped by billions of years of geologic evolution,display numerous impact craters whose distribution of size,density,and spatial arrangement reveals the celestial body's history.Identifying thes... Planetary surfaces,shaped by billions of years of geologic evolution,display numerous impact craters whose distribution of size,density,and spatial arrangement reveals the celestial body's history.Identifying these craters is essential for planetary science and is currently mainly achieved with deep learning-driven detection algorithms.However,because impact crater characteristics are substantially affected by the geologic environment,surface materials,and atmospheric conditions,the performance of deep learning models can be inconsistent between celestial bodies.In this paper,we first examine how the surface characteristics of the Moon,Mars,and Earth,along with the differences in their impact crater features,affect model performance.Then,we compare crater detection across celestial bodies by analyzing enhanced convolutional neural networks and U-shaped Convolutional Neural Network-based models to highlight how geology,data,and model design affect accuracy and generalization.Finally,we address current deep learning challenges,suggest directions for model improvement,such as multimodal data fusion and cross-planet learning and list available impact crater databases.This review can provide necessary technical support for deep space exploration and planetary science,as well as new ideas and directions for future research on automatic detection of impact craters on celestial body surfaces and on planetary geology. 展开更多
关键词 Crater detection algorithms Deep learning Different celestial bodies Impact crater databases
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Evaluation of Application Effectiveness on Ocean Salinity Satellite RFI Detection Algorithms 认领 引用
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作者 Liqiang Zhang Qingxia Li +7 位作者 Haitao Qiu Qingjun Zhang Yixin Gao Rong Jin Rui Wang Huan Zhang Zhongkai Wen Jian Zhang 《Space(Science & Technology)》 EI 2024年第1期663-673,共11页
In order to alleviate the impact of radio frequency interference(RFI)on the accuracy of ocean salinity satellite remote sensing,scholars have proposed various detection and labeling algorithms for RFI based on remote ... In order to alleviate the impact of radio frequency interference(RFI)on the accuracy of ocean salinity satellite remote sensing,scholars have proposed various detection and labeling algorithms for RFI based on remote sensing data from the SMOS satellite.However,the signals that generate RFI are diverse,and the factors that influence remote sensing observation data are complex.Existing algorithms often target specific hypothetical conditions,lacking general applicability,which frequently leads to an important gap between the nominal performance of the literature and practical applications,posing great challenges to data labeling work.To address this problem,this study conducted a comprehensive and systematic analysis of RFI simulation based on scene modeling,algorithm modeling,and RFI energy modeling.Three typical RFI detection algorithms were selected,and the simulation scene was divided into 3 typical scenes:ocean,land,and sea–land scenes,and RFI was analyzed in terms of weak,moderate,strong,and extremely strong based on energy.Through simulation analysis and evaluation of RFI detection algorithms,lookup tables for algorithm selection,detection rate,and false-positive rate have been established for different intensities of independent RFI sources and multiple nearby RFI sources in the above scenario.These lookup tables have universal guiding significance and provide reliability assurance in complex situations. 展开更多
关键词 ocean salinity satellite remote sensingscholars radio frequency interference rfi satellite rfi detection remote sensing detection labeling algorithms remote sensing observation remote sensing data smos satellitehoweverthe
Combining TDLAS and multi-fusion algorithms for methane gas concentration detection 认领 引用
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作者 SHI Guojun SONG Xinmin DONG Taiji 《Optoelectronics Letters》 EI 2024年第6期353-359,共7页
High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration inf... High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition(VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy(TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively. 展开更多
关键词 Combining TDLAS and multi-fusion algorithms for methane gas concentration detection TDLAS
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Analysis and Design of Surgical Instrument Localization Algorithm 认领 引用 被引量：4
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作者 Siyu Lu Jun Yang +4 位作者 Bo Yang Zhengtong Yin Mingzhe Liu Lirong Yin Wenfeng Zheng 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第10期669-685,共17页
With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole sy... With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy. 展开更多
关键词 Surgical navigation system surgical instruments positioning positioning mark detection algorithm matching algorithm posture analysis
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Novel approach of crater detection by crater candidate region selection and matrix-pattern-oriented least squares support vector machine 认领 引用 被引量：5
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作者 Ding Meng Cao Yunfeng Wu Qingxian 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2013年第2期385-393,共9页
Impacted craters are commonly found on the surface of planets, satellites, asteroids and other solar system bodies. In order to speed up the rate of constructing the database of craters, it is important to develop cra... Impacted craters are commonly found on the surface of planets, satellites, asteroids and other solar system bodies. In order to speed up the rate of constructing the database of craters, it is important to develop crater detection algorithms. This paper presents a novel approach to automatically detect craters on planetary surfaces. The approach contains two parts： crater candidate region selection and crater detection. In the first part, crater candidate region selection is achieved by Kanade-Lucas-Tomasi （KLT） detector. Matrix-pattern-oriented least squares support vector machine （MatLSSVM）, as the matrixization version of least square support vector machine （SVM）, inherits the advantages of least squares support vector machine （LSSVM）, reduces storage space greatly and reserves spatial redundancies within each image matrix compared with general LSSVM. The second part of the approach employs MatLSSVM to design classifier for crater detection. Experimental results on the dataset which comprises 160 preprocessed image patches from Google Mars demonstrate that the accuracy rate of crater detection can be up to 88%. In addition, the outstanding feature of the approach introduced in this paper is that it takes resized crater candidate region as input pattern directly to finish crater detection. The results of the last experiment demonstrate that MatLSSVM-based classifier can detect crater regions effectively on the basis of KLT-based crater candidate region selection. 展开更多
关键词 Crater candidate region Crater detection algorithm Kanade–Lucas–Tomasi detector Least squares support vector machine Matrixization
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A Detection Method of WLAN Security Mechanisms Based on MAC Frame Resolution 认领 引用 被引量：2
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作者 LI June YUAN Kai +5 位作者 ZHOU Liang HAN Lifang LI Ling WANG Zhihao LIU Yinbin HUANG Wenbin 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2017年第2期93-102,共10页
Security mechanism detection is not only an important content of vulnerabilities evaluation but also the foundation of key strength test for wireless local area network （WLAN）. This paper analyzes the specifications... Security mechanism detection is not only an important content of vulnerabilities evaluation but also the foundation of key strength test for wireless local area network （WLAN）. This paper analyzes the specifications of WLAN security mechanisms and points out the defects in design of security mechanisms detection algorithm based on the standards. By capturing and analyzing a large number of Beacon frames from different vendor＇s access points （APs）, we summarize the relevant fields and information elements in a Beacon frame, and present their values or status when an AP is set to every specific security mechanism. A detection algorithm of WLAN security mechanisms is proposed based on the experimental study result and the pseudo code of a reference implementation for the algorithm is designed. The validity of the algorithm is illustrated by examples, which shows it can detect every WLAN security mechanism accurately. 展开更多
关键词 IEEE 802.11 security mechanism detection algorithm MAC frame resolution vulnerabilities evaluation
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AIRS Cloud Detection Scheme Based on FOV 认领 引用
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作者 陈靖 李刚 王根 《Meteorological and Environmental Research》 2010年第2期88-90,共3页
6 hours scanning of view field was conducted by Grapes-3DVar detection system.The process is based on cloud detection,combining Grapes-3DVar system with AIRS instrument characteristics to eliminate field of view conta... 6 hours scanning of view field was conducted by Grapes-3DVar detection system.The process is based on cloud detection,combining Grapes-3DVar system with AIRS instrument characteristics to eliminate field of view contaminated by cloud,which lays a solid foundation for application of AIRS data in 3-dimensional variational assimilation system. 展开更多
关键词 AIRS Radiance Cloud contamination Mitch cloud detection algorithm China
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