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Hands-On Neural Networks with Keras

You're reading from  Hands-On Neural Networks with Keras

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789536089
Pages 462 pages
Edition 1st Edition
Languages
Author (1):
Niloy Purkait Niloy Purkait
Profile icon Niloy Purkait

Table of Contents (16) Chapters

Preface Section 1: Fundamentals of Neural Networks
Overview of Neural Networks A Deeper Dive into Neural Networks Signal Processing - Data Analysis with Neural Networks Section 2: Advanced Neural Network Architectures
Convolutional Neural Networks Recurrent Neural Networks Long Short-Term Memory Networks Reinforcement Learning with Deep Q-Networks Section 3: Hybrid Model Architecture
Autoencoders Generative Networks Section 4: Road Ahead
Contemplating Present and Future Developments Other Books You May Enjoy

Designing a CNN

Now, armed with the intuition of biological vision, we understand how neurons must be organized hierarchically, to detect simple patterns and use these to progressively build more complex patterns corresponding to real-world objects. We also know that we must implement a mechanism for spatial invariance to allow neurons to deal with similar inputs occurring at different spatial locations of a given image. Finally, we are aware that implementing a receptive field for each neuron is useful to achieve a topographical mapping of neurons to spatial locations in the real world, so that nearby neurons may represent nearby regions in the field of vision.

Dense versus convolutional layer

You will recall from the previous...

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