HYPER TUNING OF CNN BASED IMAGE CLASSIFICATION MODEL USING DIFFERENT AI BASED OPTIMIZATION TECHNIQUE

AI based image classification is the most preferable method in image processing with the development in techniques multiple method evaluation to optimized the classification model. The hyper tuning of CNN parameters is required to achieve the best performance for image classification. In this paper multiple CNN is used for classifying the standard Intel image dataset. Further methods like modified CNN, GA, WOA, MFO have been achieved to the hyper tuning parameters of CNN to improve the performance of image classification based on iterations and iteration per epochs with learning rate to solve complex problem. The Comparative results of these are discussed in the result section of the paper.