Convolutional neural networks represent a powerful class of deep learning algorithms largely used for interpreting visual data. Inspired by the structure of the human visual cortex, CNNs employ a hierarchy of convolutional layers to identify abstract features from input data. These representations subsequently processed by fully connected layers to

Deep learning has revolutionized many fields, and convolutional neural networks (CNNs) are a crucial component of this progress. CNNs are particularly well-suited for processing data with a grid-like structure, such as images and videos. They achieve this through a series of convolutional layers that apply filters to extract features from the input