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Handbook of Deep Learning Applications

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Cover of 'Handbook of Deep Learning Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Designing a Neural Network from Scratch for Big Data Powered by Multi-node GPUs
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    Chapter 2 Deep Learning for Scene Understanding
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    Chapter 3 An Application of Deep Learning in Character Recognition: An Overview
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    Chapter 4 Deep Learning for Driverless Vehicles
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    Chapter 5 Deep Learning for Document Representation
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    Chapter 6 Applications of Deep Learning in Medical Imaging
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    Chapter 7 Deep Learning for Marine Species Recognition
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    Chapter 8 Deep Molecular Representation in Cheminformatics
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    Chapter 9 A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving
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    Chapter 10 Phase Identification and Workflow Modeling in Laparoscopy Surgeries Using Temporal Connectionism of Deep Visual Residual Abstractions
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    Chapter 11 Deep Learning Applications to Cytopathology: A Study on the Detection of Malaria and on the Classification of Leukaemia Cell-Lines
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    Chapter 12 Application of Deep Neural Networks for Disease Diagnosis Through Medical Data Sets
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    Chapter 13 Why Dose Layer-by-Layer Pre-training Improve Deep Neural Networks Learning?
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    Chapter 14 Springer: Deep Learning in eHealth
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    Chapter 15 Deep Learning for Brain Computer Interfaces
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    Chapter 16 Reducing Hierarchical Deep Learning Networks as Game Playing Artefact Using Regret Matching
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    Chapter 17 Deep Learning in Gene Expression Modeling
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Citations

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Title
Handbook of Deep Learning Applications
Published by
Springer International Publishing, March 2019
DOI 10.1007/978-3-030-11479-4
ISBNs
978-3-03-011478-7, 978-3-03-011479-4
Editors

Balas, Valentina Emilia, Roy, Sanjiban Sekhar, Sharma, Dharmendra, Samui, Pijush

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 86 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 24%
Student > Bachelor 12 14%
Researcher 11 13%
Student > Master 8 9%
Lecturer 5 6%
Other 16 19%
Unknown 13 15%
Readers by discipline Count As %
Computer Science 31 36%
Engineering 19 22%
Mathematics 3 3%
Agricultural and Biological Sciences 2 2%
Psychology 2 2%
Other 13 15%
Unknown 16 19%