GANs vs. CNNs: The Power Behind AI Visual Recognition
GANs vs. CNNs: The Power Behind AI Visual Recognition Artificial Intelligence (AI) has revolutionized the way machines interpret and interact with visual data. Two key technologies driving advancements in computer vision are Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) . While both are essential in AI-driven image processing, their applications and functionalities differ significantly. Let’s explore their roles and compare how they shape modern visual recognition systems. What is a Convolutional Neural Network (CNN)? A CNN is a deep learning model designed for analyzing visual data. It mimics the way the human brain processes images, making it a powerful tool for tasks like object detection, facial recognition, and medical imaging analysis. CNNs work by applying filters to input images, detecting patterns such as edges, shapes, and textures, and then classifying them based on learned features. How CNNs Work: Convolutional Layers : Extra...