Notes on the implementation DenseNet in tensorflow.

DenseNet(Densely Connected Convolutional Networks) is one of the latest neural networks for visual object recognition that obtains state of the art results on many datasets. It's quite similar to ResNet but has some fundamental differences. This post assumes previous knowledge of neural networks(NN) and convolutions(convs). If you know how DenseNets works and interested only in tensorflow implementation feel free to jump to the second chapter or check the source code on GitHub. If you not familiar with any topics but want to get some knowledge -- I highly advise you this CS231n Stanford classes.