2026-10-30T01:19:42Zhttps://munzur-rdlopen.rawdatalibrary.net/oai/request

oai:munzur-rdlopen.rawdatalibrary.net:munzur/35222026-10-28T15:30:44Zopenairedrivercom_munzur_1col_munzur_2com_munzur_8col_munzur_154

Face recognition based on convolutional neural networkCoskun, MusabUcar, AysegulYildirim, OzalDemir, Yakupconvolutional neural networkdeep learningface recognitionsoftmax classifierFace recognition is of great importance to real world applications such as video surveillance, human machine interaction and security systems. As compared to traditional machine learning approaches, deep learning based methods have shown better performances in terms of accuracy and speed of processing in image recognition. This paper proposes a modified Convolutional Neural Network (CNN) architecture by adding two normalization operations to two of the layers. The normalization operation which is batch normalization provided acceleration of the network. CNN architecture was employed to extract distinctive face features and Softmax classifier was used to classify faces in the fully connected layer of CNN. In the experiment part, Georgia Tech Database showed that the proposed approach has improved the face recognition performance with better recognition results.Institute of Electrical and Electronics Engineers Inc.2017Conference Objecthttps://rdlopen.rawdatalibrary.net/r/munzur/3522https://doi.org/10.1109/mees.2017.8248937978-153861750-2enProceedings of the International Conference on Modern Electrical and Energy Systems, MEES 2017info:eu-repo/semantics/openAccessinfo:eu-repo/semantics/conferenceObjecthttps://munzur-rdlopen.rawdatalibrary.net/tr/items/munzur/3522