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Deep Learning Applications

Overview of attention for book
Cover of 'Deep Learning Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Trends in Deep Learning Applications
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    Chapter 2 Quasi-Newton Optimization Methods for Deep Learning Applications
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    Chapter 3 Medical Image Segmentation Using Deep Neural Networks with Pre-trained Encoders
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    Chapter 4 Ensemble of 3D Densely Connected Convolutional Network for Diagnosis of Mild Cognitive Impairment and Alzheimer’s Disease
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    Chapter 5 Detecting Work Zones in SHRP2 NDS Videos Using Deep Learning Based Computer Vision
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    Chapter 6 Action Recognition in Videos Using Multi-stream Convolutional Neural Networks
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    Chapter 7 Deep Active Learning for Image Regression
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    Chapter 8 Deep Learning Based Hazard Label Object Detection for Lithium-ion Batteries Using Synthetic and Real Data
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    Chapter 9 Enabling Robust and Autonomous Materialhandling in Logistics Through Applied Deep Learning Algorithms
Attention for Chapter 8: Deep Learning Based Hazard Label Object Detection for Lithium-ion Batteries Using Synthetic and Real Data
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Citations

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Chapter title
Deep Learning Based Hazard Label Object Detection for Lithium-ion Batteries Using Synthetic and Real Data
Chapter number 8
Book title
Deep Learning Applications
Published by
Springer, Singapore, February 2020
DOI 10.1007/978-981-15-1816-4_8
Book ISBNs
978-9-81-151815-7, 978-9-81-151816-4
Authors

Anneliese Schweigert, Christian Blesing, Christoph M. Friedrich, Schweigert, Anneliese, Blesing, Christian, Friedrich, Christoph M.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Unknown 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Unknown 1 50%

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