Development of Skip Connection in Deep Neural Networks for Computer Vision and Medical Image Analysis: A Survey

arXiv:2405.01725v1 Announce Type: cross
Abstract: Deep learning has made significant progress in computer vision, specifically in image classification, object detection, and semantic segmentation. The skip connection has played an essential role in the architecture of deep neural networks,enabling easier optimization through residual learning during the training stage and improving accuracy during testing. Many neural networks have inherited the idea of residual learning with skip connections for various tasks, and it has been the standard choice for designing neural networks. This …

analysis arxiv computer computer vision cs.cv cs.lg development eess.iv image medical networks neural networks survey type vision