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Register a new userUsing The System of Identifying People Based on their Facial Expressions to Design the Automated Checking System for Students
استخدام نظام التعرف على الأشخاص بالاعتماد على تعابير الوجه في تصميم نظام التفقد الآلي للطلبة
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يقدم البحث تصميماً لنظام تفقد آلي للطلبة، يقوم النظام بالتقاط صورة للطالب ثم استخلاص ملامح الوجه الأساسية، تم تدريب الشبكة باستخدام خوارزمية الانتشار العكسي، إذ تم توليد قاعدة بيانات تدريبية لكل طالب، مكونة من 15 عينة تدريبية له لمرة واحدة في بداية الفصل الدراسي، كل عينة تحتوي تعابير الوجه اللازمة للتعرف على طالب، تُدرب الشبكة العصبونية على قاعدة بيانات الطلبة من أجل الحصول على شبكة عصبونية مدربة قادرة على التعرف على طلاب كل فئة بالاعتماد على ملامحهم، وبالتالي معرفة من حضر الجلسة ممن لم يحضر، تم تزويد النظام المصمم لهذا الغرض بالشبكة المدربة، يقدم النظام إمكانية إجراء التفقد الآلي للطلاب حسب فحوى الدراسة مع التنبيه في حال وجود صورة لطالب لا ينتمي لنفس المجموعة.
The research presents a design for an automated checking system for students. The system takes a picture of the student, then it extracts his/her basic facial features. The network was trained using the reverse spreading algorithm. If a training database is generated for each student consisting of 15 training samples contained of the necessary facial expressions to identify the student for one time at the beginning of the semester, then the neural network will be trained on students database to obtain a trained neural network able to identify the students of each category depending on their physical appearance. That will result in knowing who attends and who does not attend the session. The system designed for this purpose was supplied with the trained network. The system provides the possibility of automated checking for students according to the content of the study giving the alarm in case of the existence of the picture of a student who does not belong to the same group.
References used
Nawi, Nazri. Mohd. ;Khan, Abdullah. ; Rehman, M.Z. , A New Levenberg Marquardt based Back Propagation Algorithm Trained with Cuckoo Search, Maturitas Procedia Technology. Volume 11, 2013,Pages 18-23
Sridevi, K.; Sivaraman, E.; Mullai, P.; Back propagation neural network modelling of biodegradation and fermentative biohydrogen production using distillery wastewater in a hybrid upflow anaerobic sludge blanket reactor, Bioresource Technology, In Press, Corrected Proof, 2014,Available online 27 March
[Fiszelew, A.; Britos, P.; Perichisky, G.; García-Martínez, R, Automatic Generation of Neural Networks based on Genetic Algorithms .Revista Eletrônica de Sistemas de Informação, 2003, 2(1), 1-7 .[19
(Sammany, M.; Abd-Elal, L .F.; Ismail, A .I., Sweilam; N .H, Studying the Neural Networks and Mathematical Applications, "MSc Thesis in Computational Mathematics : [2006]" . (Cairo University -Cairo, Egypt) (25
Jeremy, Kun., Neural Networks and the Backpropagation Algorithm, Math ∩ Programming Posted on December 9,2012
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The aim of the work is to improve the performance of the WLD
descriptor using Gabor filters in a preprocessing stage. The
performance of the improved descriptor will be compared with the
performance of the LBP descriptor(a widely used descriptor i
n FER
researches). This performance will be achieved using the extremely
used expert system SVM besides the expert systems CSD and MLP.
التعرف على تعابير الوجه
النماذج الثنائية المحلية
واصف ويبر المحلي
نماذج غير المحلية الثنائية
واصف ويبر-غيبر المحلي
مرشح غيبر
الشبكة العصبونية متعددة الطبقات
أداة الأشعة الداعمة
مسافة تشي التربيعية
FER-Facial Expression Recognition
LBP-Local Binary Pattern
WLD-Weber Local Descriptor
LGBP-Local Gabor Binary Pattern
WGLD-Weber Gabor Local Descriptor. Gabor filter
MLP-Multi Layer Perceptron
SVM- Support Vector Machine
CSD- Chi squared distance
المزيد..
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