Attention Based Network

Attention-based networks are a class of neural networks designed to selectively focus on the most relevant information within input data, improving efficiency and accuracy in various tasks. Current research emphasizes the development of novel attention mechanisms, often integrated into transformer, convolutional, or hybrid architectures, to enhance performance in areas like object detection, visual navigation, and pose estimation. These networks are proving highly effective across diverse applications, from medical image analysis and video enhancement to natural language processing and robotics, driving advancements in fields requiring sophisticated information processing.

Papers