Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature - chaurasia, Rahul; Agrawal, Jitendra (International Journal of Computer Sciences and Engineering, 2025)
Most of sentiment based image classification approaches have done lots of complex calculation such as number of feature was collected for identifying correct class. In case of supervised learning models prediction of sentiment class for the unknown image leads to false alarm. So this work take facial input image features and find the sentiment of image by genetic approach. In this work grouping of various sort of information was managed without bargaining the security using genetic algorithm TLBO teacher Learning Based Optimization. Experiment was done on real dataset of JAFEE Images. Results show that execution time for the sentiment identification of image information was low. Here proposed work was capable to classify input data with high accuracy as compared to previous machine learning approaches