این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
International Journal of Engineering، جلد ۳۶، شماره ۸، صفحات ۱۵۴۸-۱۵۵۵
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Feature Extraction from Several Angular Faces Using a Deep Learning Based Fusion Technique for Face Recognition
چکیده انگلیسی مقاله Due to its non-interfering nature, face recognition has been the most suitable technology for designing biometric systems in recent years.  This technology is used in various industries, such as health care, education, security, and surveillance. Facial recognition technology works best when a person is looking straight into the camera. On the contrary, the performance of facial recognition degrades when encountered with an angled facial image, because they are generally trained using images of a full face. The purpose of this paper is to estimate the feature vector of a full face image when there are several angular facial images of the same person, one example being angular faces in a video. This method extracts the basic features of a facial image using the non-negative matrix factorization (NMF) method. Then, the feature vectors are fused using a generative adversarial network (GAN) to estimate the feature vector associated with the frontal image. The experimental results on the angular images of the FERET dataset show that the proposed method can significantly improve the accuracy of facial  recognition technology methods.
کلیدواژه‌های انگلیسی مقاله Feature Extraction,Angled face recognition,Fusion of feature vectors,Generative Adversarial Neural Networks
نویسندگان مقاله E. Charoqdouz |
Faculty of Computer Engineering, Shahrood University of Technology, Shahrood, Iran

H. Hassanpour |
Faculty of Computer Engineering, Shahrood University of Technology, Shahrood, Iran

نشانی اینترنتی https://www.ije.ir/article_173247_e5ccb1be5ea85859d3ad77a840025383.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات