Merhaba Misafir

A comparison of deep learning based architecture with a conventional approach for face recognition problem


This paper addresses a new approach for face recognition problem based on deep learning strategy. In order to verify the performance of the proposed approach, it is compared with a conventional face recognition method by using various comprehensive datasets. The conventional approach employs Histogram of Gradient (HOG) algorithm to extract features and utilizes a multi-class Support Vector Machine (SVM) classifier to train and learn the classification. On the other hand, the proposed deep learning based approaches employ a Convolutional Neural Network (CNN) based architecture and also offer both a SVM and Softmax classifiers respectively for the classification phase. Results reveal that the proposed deep learning architecture using Softmax classifier outperform conventional method by a substantial margin. As well as, the deep learning architecture using Softmax classifier also outperform SVM in almost all cases.

Yayınlandığı Kaynak : Communications, Series A2-A3 Physics, Engineering Physics, Electronix Engineering and Astronomy
  • Yıl : 2019
  • DOI : 10.33769/aupse.529575
  • Cilt : 61
  • ISSN : 1303-6009
  • Sayı : 2
  • Sayfa Aralığı : 129-149
  • IO Kayıt No : 113171
  • Yayıncı : Ankara Üniversitesi Fen Fakültesi