Comprehensive Analysis of Machine Learning Algorithms for Face Detection
Bhavana1, V. Jagan Naveen2, K. Krishna Kishore3
1Bhavana, ECE, GMR Institution of Technology,Rajam, India.
2V. Jagan Naveen, ECE, GMR Institution of Technology, India.
3K. Krishna Kishore, ECE, GMR Institution of Technology,Rajam, India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 2479-2482 | Volume-8 Issue-10, August 2019 | Retrieval Number: J95420881019/2019©BEIESP | DOI: 10.35940/ijitee.J9542.0881019
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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: Face detection is the most common application used in security system, cameras, fun face filter apps, etc. many techniques and algorithms are introduced by developers for face detection in real time but all techniques or algorithms does not give best results while applying on all ranges of processors. In this, three machine learning algorithms i.e. Histogram of Oriented Gradient, Haar cascade classifier and deep neural networks implemented on different processors for verifying processing speed of each algorithm on the different processor.
Keywords: Deep neural network, Haar cascade classifier, Histogram of oriented gradient, Machine learning.
Scope of the Article: Machine Learning