<ul><li>Researchers found that as deep neural networks become deeper, they start to perform worse due to optimization difficulties.</li><li>To overcome this, the authors introduced a new architecture called Residual Network (ResNet).</li><li>ResNet allows layers to learn the difference between the input and the output, enabling successful training of deeper networks.</li><li>ResNets achieve state-of-the-art accuracy on various tasks.</li></ul>

(Analysis) Deep Residual Learning for Image Recognition

Discover more