Enhancement of Face Recognition using Deep Learning
T. R. Rajesh1, Panthagani Vijaya Babu2, Shaik Shabbir Hussain3, K Venkata Subramanyam4
1T. R. Rajesh, Asst. Prof, CSE, Vignan’s Foundation for Science, Technology & Research, Guntur, Andhra Pradesh, India.
2Pathagani Vijaya Babu, Asst. Prof, CSE, Vignan’s Foundation for Science, Technology & Research, Guntur, Andhra Pradesh ,India.
3Shaik Shabbir Hussain, Asst. Prof, CSE, Vignan’s Foundation for Science, Technology & Research, Guntur, Andhra Pradesh , India.
4K .Venkata Subramanyam, Asst. Prof, CSE, Vignan’s Foundation for Science, Technology & Research, Guntur, Andhra Pradesh , India.
Manuscript received on November 21, 2019. | Revised Manuscript received on December 30, 2019. | Manuscript published on December 30, 2019. | PP: 5072-5075 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4214129219/2019©BEIESP | DOI: 10.35940/ijeat.B4214.129219
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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.