CNNs vs. GANs: Understanding Key Differences in Deep Learning
Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) are two pivotal architectures in deep learning. While CNNs excel in image recognition and classification, GANs are renowned for generating realistic data samples. This article explores their key differences, structures, functionalities, and example models, providing insights into how these powerful tools can be leveraged in various applications to drive innovation and achieve breakthroughs.