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Deep Neural Evolution

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Cover of 'Deep Neural Evolution'

Table of Contents

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    Book Overview
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    Chapter 1 Evolutionary Computation and Meta-heuristics
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    Chapter 2 A Shallow Introduction to Deep Neural Networks
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    Chapter 3 On the Assessment of Nature-Inspired Meta-Heuristic Optimization Techniques to Fine-Tune Deep Belief Networks
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    Chapter 4 Automated Development of DNN Based Spoken Language Systems Using Evolutionary Algorithms
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    Chapter 5 Search Heuristics for the Optimization of DBN for Time Series Forecasting
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    Chapter 6 Particle Swarm Optimization for Evolving Deep Convolutional Neural Networks for Image Classification: Single- and Multi-Objective Approaches
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    Chapter 7 Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming
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    Chapter 8 Fast Evolution of CNN Architecture for Image Classification
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    Chapter 9 Discovering Gated Recurrent Neural Network Architectures
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    Chapter 10 Investigating Deep Recurrent Connections and Recurrent Memory Cells Using Neuro-Evolution
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    Chapter 11 Neuroevolution of Generative Adversarial Networks
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    Chapter 12 Evolving Deep Neural Networks for X-ray Based Detection of Dangerous Objects
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    Chapter 13 Evolving the Architecture and Hyperparameters of DNNs for Malware Detection
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    Chapter 14 Data Dieting in GAN Training
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    Chapter 15 One-Pixel Attack: Understanding and Improving Deep Neural Networks with Evolutionary Computation
Attention for Chapter 8: Fast Evolution of CNN Architecture for Image Classification
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Citations

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Chapter title
Fast Evolution of CNN Architecture for Image Classification
Chapter number 8
Book title
Deep Neural Evolution
Published by
Springer, Singapore, January 2020
DOI 10.1007/978-981-15-3685-4_8
Book ISBNs
978-9-81-153684-7, 978-9-81-153685-4
Authors

Ali Bakhshi, Stephan Chalup, Nasimul Noman, Bakhshi, Ali, Chalup, Stephan, Noman, Nasimul

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Student > Bachelor 2 13%
Unspecified 1 7%
Lecturer 1 7%
Professor 1 7%
Other 1 7%
Unknown 7 47%
Readers by discipline Count As %
Computer Science 4 27%
Engineering 3 20%
Unspecified 1 7%
Unknown 7 47%