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Historical Arabic Images Classification and Retrieval Using Siamese Deep Learning Model 认领 引用
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作者 Manal M.Khayyat Lamiaa A.Elrefaei Mashael M.Khayyat 《Computers, Materials & Continua》 SCIE EI 2022年第7期2109-2125,共17页
Classifying the visual features in images to retrieve a specific image is a significant problem within the computer vision field especially when dealing with historical faded colored images.Thus,there were lots of eff... Classifying the visual features in images to retrieve a specific image is a significant problem within the computer vision field especially when dealing with historical faded colored images.Thus,there were lots of efforts trying to automate the classification operation and retrieve similar images accurately.To reach this goal,we developed a VGG19 deep convolutional neural network to extract the visual features from the images automatically.Then,the distances among the extracted features vectors are measured and a similarity score is generated using a Siamese deep neural network.The Siamese model built and trained at first from scratch but,it didn’t generated high evaluation metrices.Thus,we re-built it from VGG19 pre-trained deep learning model to generate higher evaluation metrices.Afterward,three different distance metrics combined with the Sigmoid activation function are experimented looking for the most accurate method formeasuring the similarities among the retrieved images.Reaching that the highest evaluation parameters generated using the Cosine distance metric.Moreover,the Graphics Processing Unit(GPU)utilized to run the code instead of running it on the Central Processing Unit(CPU).This step optimized the execution further since it expedited both the training and the retrieval time efficiently.After extensive experimentation,we reached satisfactory solution recording 0.98 and 0.99 F-score for the classification and for the retrieval,respectively. 展开更多
关键词 Visual features vectors deep learning models distance methods similar image retrieval
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Diagnosing Student Learning Problems in Object Oriented Programming 认领 引用
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作者 Hana Al-Nuaim Arwa Allinjawi +1 位作者 Paul Krause Lilian Tang 《Computer Technology and Application》 2011年第11期858-865,共8页
Students often face difficulties while taking basic programming courses due to several factors. In response, research has presented subjective assessments for diagnosing learning problems to improve the teaching of pr... Students often face difficulties while taking basic programming courses due to several factors. In response, research has presented subjective assessments for diagnosing learning problems to improve the teaching of programming in higher education. In this paper, the authors propose an Object Oriented conceptual map model and organize this approach into three levels： constructing a Concept Effect Propagation Table, constructing Test Item-Concept Relationships and diagnosing Student Learning Problems with Matrix Composition. The authors＇ work is a modification of the approaches of Chert and Bai as well as Chu et al., as the authors use statistical methods, rather than fuzzy sets, for the authors＇ analysis. This paper includes a statistical summary, which has been tested on a small sample of students in King Abdulaziz University, Jeddah, Saudi Arabia, illustrating the learning problems in an Object Oriented course. The experimental results have demonstrated that this approach might aid learning and teaching in an effective way. 展开更多
关键词 Higher education programming learning difficulties object oriented programming conceptual model.
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