Hitchhiker’s Guide to Residual Networks (ResNet) in Keras
https://towardsdatascience.com/hitchhikers-guide-to-residual-networks-resnet-in-keras-385ec01ec8ff
Photo by Andrés Canchón on UnsplashVery deep neural networks are hard to train as they are more prone to vanishing or exploding gradients. To solve this problem, the activation unit from a layer could be fed directly to a deeper layer of the network, which is termed as a skip connection.
This forms the basis of residual networks or ResNets. This post will introduce the basics the residual networks before implementing one in Keras.
Hitchhiker’s Guide to Residual Networks (ResNet) in Keras
Apr 8, 2019, 2:56pm UTC
https://towardsdatascience.com/hitchhikers-guide-to-residual-networks-resnet-in-keras-385ec01ec8ff
> Photo by Andrés Canchón on UnsplashVery deep neural networks are hard to train as they are more prone to vanishing or exploding gradients. To solve this problem, the activation unit from a layer could be fed directly to a deeper layer of the network, which is termed as a skip connection.
> This forms the basis of residual networks or ResNets. This post will introduce the basics the residual networks before implementing one in Keras.