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
October 31, 2024
August 24, 2024
April 12, 2024
March 25, 2024
March 15, 2024
February 28, 2024
December 3, 2023
August 29, 2023
July 14, 2023
March 21, 2023
March 20, 2023
March 7, 2023
March 3, 2023
November 27, 2022
October 20, 2022
September 11, 2022
June 16, 2022
June 2, 2022
June 1, 2022