Human Emotion Identification Using Feed Forward Neural Network with Backpropagation and Bayesian Regularized Backpropagation Algorithm
Sofia R1, Sivakumar D2
1R.Sofia. Department of Electronics and Instrumentation Annamalai University, Tamil Nadu, India.
2Dr.D. Sivakumar Department of Electronics and Instrumentation Engineering, Annamalai University, Tamil Nadu, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 1163-1165 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8352088619/2019©BEIESP | DOI: 10.35940/ijeat.F8352.088619
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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: In this work, initially the human face will be detected. Then the facial features will be extracted and classified into different expressions. Here two types of algorithm viz. used in Feed Forward neural network(FFNN), ie., Backpropagation(BP) Algorithm and Bayesian Regularization Algorithm. After evaluating Bayesian regularized Backpropagation Algorithm (BR) is found to be better suited for automatic facial expression recognition than Backpropagation algorithm(BP), and the performance is evaluate using various metrics.
Keywords: Backpropagation, Bayesian regularization, Feed forward neural network, Facial expression recognition, Feature extraction.