Human action recognition using genetic algorithms and convolutional neural networks

Conference/Journal
Pergamon
Authors
Earnest Paul Ijjina C. Krishna Mohan
BibTex
Abstract
Abstract In this paper, an approach for human action recognition using genetic algorithms (GA) and deep convolutional neural networks (CNN) is proposed. We demonstrate that initializing the weights of a convolutional neural network (CNN) classifier based on solutions generated by genetic algorithms (GA) minimizes the classification error. A gradient descent algorithm is used to train the CNN classifiers (to find a local minimum) during fitness evaluations of GA chromosomes. The global search capabilities of genetic algorithms and ...