Translations:Deep Residual Learning for Image Recognition/23/en

ResNet is one of the most cited and influential papers in deep learning. The residual connection became a fundamental building block adopted in virtually every subsequent deep architecture, including Transformers (which use residual connections around each attention and feed-forward sublayer), DenseNets, U-Nets, and modern convolutional architectures. The insight that identity mappings ease optimization in deep networks profoundly shaped both theoretical understanding and practical architecture design.