Face Recognition using Deep Neural Networks


Amirhosein Dastgiri, Pouria Jafarinamin,Sami Kamarbaste,Mahdi Gholizade,




face mode,deep neural network,deep learning,


Face recognition is one of the most important issues in the machine vision, which has many applications in the industry and other issues related to the vision of the machine. There are many algorithms in the field of machine learning to detect facial expressions. In recent years, deep neural networks are one of the areas of research. Because of its excellent performance, this technique is widely used in face recognition. Facial features are useful for a variety of tasks, and the application of deep neural network is very fast. In this paper, a method for recognition of facial expressions is presented using the features of the deep neural network. A deep neural network is used to summarize images and classify them. The proposed model focuses on identifying the faces of a person from a single image. The work algorithm is a multilayer neural network with a deep learning concept. The results show that in some cases, the recognition rate is very high.


I.A. Kortylewski, B. Egger and A. Schneider.Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems. Computer Vision and Pattern Recognition (CVPR), 2018.
II.Byeon YH, Kwak KC. Facial expression recognition using 3d convolutional neural network. Int J Adv Comput Sci Appl 5(12):107-112, 2014.
III.C. Benjamin and M. Ennio. Mitigation of effects of occlusion on object recognition with deep neural networks through low level image completion,”Computational Intelligence and Neuroscience, vol. 2016, Article ID 6425257, 15 pages, 2016.
IV.Chen, Xue-wen, Melih Aslan, Kunlei Zhang, and Thomas Huang.Learning multi-channel deep feature representations for face recognition”, In Feature Extraction: Modern Questions and Challenges, pp. 60-71, 2015.
V.Fakhari, Ali; Moghadam, Amir Masoud Eftekhari. Combination of classification and regression in decision tree for multi-labeling image annotation” Applied Soft Computing Volume 13 issue 2, 2013.
VI.Guosheng Hu and Xiaojiang Peng. Frankenstein: Learning deep face representations using small data”, IEEE Transactions on Image Processing, 2017.
VII.H.Xiong, S.Szedmak and J. Piater, “ Scalable, Accurate Image Annotation with Joint SVMs and Output Kernels, Neurocomputing”, Vol., No. 2015.
VIII.Hansen, M. F. , Smith, M. , Smith, L. , Salter, M. , Baxter, E. , Farish, M. and Grieve, B. and AB Agri, SRUC, Manchester University, Towards on-farm pig face recognition using convolutional neural networks.
Computers in Industry,98. pp. 145-152. ISSN 0166-3615 Available from: http://eprints.uwe.ac.uk/35276, 2018.
IX.J. Zeng, X. Zhao, Q. Chuanbo et al. Single sample per person face recognition based on deep convolutional neural network,” in Proceedings of IEEE International Conference on Computer and Communications (ICCC), pp. 1647–1651, Chengdu, China, December, 2017.
X.J. Zeng, X. Zhao, Y. Zhai, J. Gan, Z. Lin, and C. Qin. A novel expanding sample method for single training sample face recognition,” in Proceedings of International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), pp. 33–37, Ningbo, China, , 2017.
XI.Jing Zhang, Yaxin Zhao, Da Li, Zhihua Chen, and Yubo Yuan. A novel image annotation model based on content representation with multi-layer segmentation.Neural Comput. Appl. 26, 6,1407-1422.
DOI=http://dx.doi.org/10.1007/s00521-014-1815-6,. 2015.
XII.Jing Zhang• Yaxin Zhao• Da Li “A novel image annotation model based on content representation with multi-layer segmentation” The Natural Computing Applications Forum, 2015.
XIII.Jiwei Hu; Kin-Man Lam “An efficient two-stage framework for image annotation” Pattern Recognition Volume 46 issue 3, 2013.
XIV.K. Zhang, Z. Zhang, Z. Li, and Y. Qiao, “Joint face detection and alignment using multitask cascaded convolutional networks,” IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1499-1503, 2016.
XV.L.Agapito et al. “Mixing Low-Level and Semantic Features for Image Interpretation A Framework and a Simple Case Study”: ECCV 2014 Workshops, Part II, LNCS 8926, pp. 283–298.DOI: 10.1007/978-3-319-16181-520, 2015.
XVI.M.Saraswathi and S. Sivakumari.Evaluation of PCA and LDA techniques for Face recognition using ORL face database”, (IJCSIT) International Journal of Computer Science and Information Technologies, Volume 6 (1), 2015, pp. 810-813, 2015.
XVII.Nur Ateqah Binti Mat Kasim, Nur Hidayah Binti Abd Rahman, Zaidah Ibrahim, Nur Nabilah Abu Mangshor. Celebrity Face Recognition using Deep Learning. Indonesian Journal of Electrical Engineering and Computer Science.Vol. 12, No. 2, pp. 476~481, 2018.
XVIII.S. S. Farfade, M. J. Saberian, and L.-J. Li, “Multi-view face detection using deep convolutional neural networks ,” in Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, pp. 643-650: ACM, 2015.
XIX.S. S. Farfade, M. J. Saberian, and L.-J. Li. Multi-view face detection using deep convolutional neural networks,” in Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, pp. 643-650: ACM, 2015.
XX.Savath Saypadith and Supavadee Aramvith.Real-Time Multiple Face Recognition using Deep Learning on Embedded GPU System. Proceedings,APSIPA Annual Summit and Conference 201812-15 November, 2018.
XXI.Shraddha Arya and Arpit Agrawal.Face Recognitionwith Partial Face Recognition and Convolutional Neural Network. International Journal of Advanced Research in Computer Engineering & Technology
(IJARCET)Volume 7, Issue 1, 2278–1323, 2018.
XXII.Y. Li, W. Shen, X. Shi, and Z. Zhang.Ensemble of randomized linear discriminant analysis for face recognition with single sample per person,” in Proceedings of IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, pp. 1–8, Shanghai, 2013.
XXIII.Zhiming Qian, Ping Zhong, Jia Chen, Integrating Global and Local Visual Features with Semantic Hierarchies for Two-Level Image Annotation,Neurocomputing,http://dx.doi.org/10.1016/j.neucom. 07.094
, 2015.
Amirhosein Dastgiri, Pouria Jafarinamin, Sami Kamarbaste, Mahdi Gholizade View Download