Investigation of Efficient Approaches and Applications for Image Classification Through Deep Learning

Deep learning has achieved significant success in image classification tasks. This study explores and compares efficient approaches for image classification using Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) within the context of deep learning. The primary goal is to enhance our understanding of the effectiveness of these architectures for image classification tasks. The research concludes with a comparative analysis of different methods employed, highlighting their strengths, weaknesses, and potential applications in blended learning and Decision Support Systems for the Indian Penal Code (IPC).