CNN Network

Convolutional Neural Networks (CNNs) are a class of deep learning models designed for processing grid-like data, primarily images, by leveraging convolutional layers to extract hierarchical features. Current research emphasizes improving CNN performance through architectural innovations like incorporating self-attention mechanisms and hybrid models combining CNNs with other architectures such as Transformers and recurrent networks, as well as addressing challenges in weakly supervised learning and handling high-resolution data. These advancements are significantly impacting diverse fields, from medical image analysis (e.g., disease detection, segmentation) and industrial applications (e.g., defect detection) to environmental monitoring and even fundamental physics research.