Computer Vision With ResNet

In December of 2015, a paper was published that rocked the deep learning world. This paper is widely regarded as one of the most influential papers in modern deep learning and has been cited over 110,000 times. The prevailing wisdom of the time suggested adding more layers to neural networks would lead to better results. But researchers observed that the accuracy of deep networks would increase up to a saturation point before levelling off. In addition to that, an unusual phenomenon was observed: Adding layers to an already deep network, the training error would actually increase.