Image classification using cnn

Image classification using Convolutional Neural Networks (CNNs) and deep learning involves training a model to automatically categorize images into predefined classes. CNNs are particularly effective for this task due to their ability to capture spatial hierarchies in images through convolutional layers, which apply filters to extract features like edges, textures, and patterns. These features are then passed through pooling layers to reduce dimensionality, followed by fully connected layers to make predictions. Deep learning enhances this process by using multiple layers to learn increasingly complex and abstract features, enabling the model to achieve high accuracy in identifying and classifying images.