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Advanced Deep Learning with Keras
book

Advanced Deep Learning with Keras

by Rowel Atienza, Neeraj Verma, Valerio Maggio
October 2018
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 20m
English
Packt Publishing
Content preview from Advanced Deep Learning with Keras

Chapter 2. Deep Neural Networks

In this chapter, we'll be examining deep neural networks. These networks have shown excellent performance in terms of the accuracy of their classification on more challenging and advanced datasets like ImageNet, CIFAR10, and CIFAR100. For conciseness, we'll only be focusing on two networks, ResNet [2][4] and DenseNet [5]. While we will go into much more detail, it's important to take a minute to introduce these networks:

ResNet introduced the concept of residual learning which enabled it to build very deep networks by addressing the vanishing gradient problem in deep convolutional networks.

DenseNet improved the ResNet technique further by allowing every convolution to have direct access to inputs, and lower layer ...

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Publisher Resources

ISBN: 9781788629416Supplemental Content