In their 2015 publication “Deep Residual Learning for Image Recognition,” Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun created a particular kind of neural network known as ResNet or Residual Network. — Every consecutive winning architecture uses more layers in a deep neural network to lower the error rate after the first CNN-based architecture (AlexNet) that won the ImageNet 2012 competition. This is effective for smaller numbers of layers, but when we add more layers, a typical deep learning issue known as…