Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are a specialized class of artificial neural networks designed to process and analyze visual data, particularly images and videos. They are inspired by the biological visual cortex's structure and function in animals and have revolutionized computer vision tasks such as image classification, object detection, and semantic segmentation. CNNs work by applying a series of filters or kernels to input data, allowing them to detect patterns, features, and edges within images, which are then processed through multiple convolutional, pooling, and fully connected layers to extract high-level abstract representations. These networks can learn from large-scale datasets and improve their performance over time, making them an essential component of artificial intelligence (AI) and deep learning systems in electronics and computers for various applications, including facial recognition, autonomous driving, medical imaging, and augmented reality.