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Facial Recognition using Deep Learning
Gaurav Dubey1, Sanket Sharma2, Shashwat Pal3, Shubham Agrawal4

1Dr. Gaurav Dubey, Professor, ABES Engineering College, Ghaziabad (Uttar Pradesh), India.
2Sanket Sharma, B. Tech. ABES Engineering College, Branch Computer Science College, Ghaziabad (Uttar Pradesh), India.
3Shashwat Pal, B. Tech. ABES Engineering College, Computer Science College, Ghaziabad (Uttar Pradesh), India.
4Shubham Agrawal, B. Tech. ABES Engineering College, Branch Computer Science College, Ghaziabad (Uttar Pradesh), India.

Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 367-371 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7124068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Our aim in this paper is to increase the accuracy of existing facial recognition system on a comparative smaller dataset as per the requirements of present day. Namely in sensitive regions. The methodology that has been adopted is by combining more than one algorithms. The feature detection capability of harr cascade along with Ada boost to fetch to Bilinear CNN so that on a comparative smaller dataset can produce comparative result as on bigger dataset.
Keywords: Deep Learning, CNN, Bilinear CNN, RNN, PCA.

Scope of the Article: Deep Learning