Image Recognition

Image recognition, the automated identification of objects within images, aims to develop robust and efficient systems for various applications. Current research focuses on improving accuracy and efficiency across diverse tasks, including fine-grained recognition, garbage classification, and facial expression analysis, often employing convolutional neural networks (CNNs), vision transformers (ViTs), and generative adversarial networks (GANs). These advancements are driving progress in fields ranging from environmental monitoring and medical diagnosis to autonomous vehicles and assistive technologies, with a strong emphasis on addressing challenges like limited data, computational cost, and adversarial attacks.