Deep Learning Algorithms

Cover
Title Page
Copyright
DECLARATION
ABOUT THE EDITOR
TABLE OF CONTENTS
List of Contributors
List of Abbreviations
Preface
Section 1: Methods and Approaches for Deep Learning
	Chapter 1 Advancements in Deep Learning Theory and Applications: Perspective in 2020 and Beyond
		Abstract
		Introduction
		Deep Network Topologies
		Application of Deep Learning
		Modern Deep Learning Platforms
		Training Algorithms
		Routine Challenges of Deep Learning
		Available Open-Source Datasets
		References
	Chapter 2 Deep Ensemble Reinforcement Learning With Multiple Deep Deterministic Policy Gradient Algorithm
		Abstract
		Introduction
		Background
		Methods
		Results and Discussion
		Conclusions
		References
	Chapter 3 Dynamic Decision-Making For Stabilized Deep Learning Software Platforms
		Abstract
		Introduction
		Stabilized Control for Reliable Deep Learning Platforms
		The Use of Lyapunov Optimization for Deep Learning Platforms
		Emerging Applications
		Conclusions
		Acknowledgements
		References
	Chapter 4 Deep Learning For Hyperspectral Data Classification Through Exponential Momentum Deep Convolution Neural Networks
		Abstract
		Introduction
		Feature Learning
		Structure Design of Hyperspectral Data Classification Framework
		Exponential Momentum Gradient Descent Algorithm
		Experiment and Analysis
		Conclusion
		Acknowledgments
		References
	Chapter 5 Ensemble Network Architecture for Deep Reinforcement Learning
		Abstract
		Introduction
		Related Work
		Ensemble Methods for Deep Reinforcement Learning
		Experiments
		Conclusion
		References
Section 2: Deep Learning Techniques Applied in Biology
	Chapter 6 Fish Detection Using Deep Learning
		Abstract
		Introduction
		Literature Review
		Materials and Methods
		Data Augmentation
		Results and Discussion
		Conclusion
		Acknowledgments
		References
	Chapter 7 Can Deep Learning Identify Tomato Leaf Disease?
		Abstract
		Introduction
		Related Work
		Materials and Methods
		Experiments and Results
		Conclusion
		Acknowledgments
		References
	Chapter 8 Deep Learning For Plant Identification In Natural Environment
		Abstract
		Introduction
		Proposed Bjfu100 Dataset and Deep Learning Model
		Experiments and Results
		Resnet26 on Flavia Dataset
		Conclusion
		Acknowledgments
		References
	Chapter 9 Applying Deep Learning Models to Mouse Behavior Recognition
		Abstract
		Introduction
		The Mouse Behavior Dataset
		Experiments and Results
		Conclusions
		Acknowledgements
		References
Section 3: Deep learning Applications in Medicine
	Chapter 10 Application of Deep Learning in Neuroradiology: Brain Hemorrhage Classification Using Transfer Learning
		Abstract
		Introduction
		Related Work
		Convolutional Neural Network
		Transfer Learning
		Materials and Methods
		Results and Discussion
		Limitations
		Conclusion
		References
	Chapter 11 A Review of the Application of Deep Learning in Brachytherapy
		Abstract
		Introduction
		Organ Delineation and Segmentation
		Segmentation and Reconstruction of the Applicator (Interstitial Needles)
		Dose Calculation
		Application of Treatment Planning System
		Others
		Conclusions
		References
	Chapter 12 Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification
		Abstract
		Introduction
		Materials and Methods
		Results and Discussion
		Conclusion
		Acknowledgments
		References
	Chapter 13 Deep Learning Algorithm For Brain-Computer Interface
		Abstract
		Introduction
		Critical Review of the Related Literature
		Comparison of Classification Algorithms
		Discussion
		Methodology
		Conclusion
		References
Section 4: Deep Learning in Pattern Recognition Tasks
	Chapter 14 The Application of Deep Learning In Airport Visibility Forecast
		Abstract
		Introduction
		Deep Learning
		The Establishment of Prediction Model
		Predictive Effect Test
		Conclusions
		References
	Chapter 15 Hierarchical Representations Feature Deep Learning For Face Recognition
		Abstract
		Introduction
		Images Preprocessing
		Feature Extraction
		Designing the Classifiers of Supervised Learning
		Designing the Classifier Combining Unsupervised and Supervised Learning
		Experiments
		Conclusion
		Acknowledgements
		References
	Chapter 16 Review of Research on Text Sentiment Analysis Based on Deep Learning
		Abstract
		Introduction
		Brief Review on the Research Progress of Text Sentiment Analysis
		Introduction to Text Sentiment Analysis Based on Deep Learning
		Summary and Prospect
		References
	Chapter 17 Classifying Hand Written Digits With Deep Learning
		Abstract
		Introduction
		Digit Classification with Deep Networks
		Experiment
		Conclusions
		References
	Chapter 18 Bitcoin Price Prediction Based on Deep Learning Methods
		Abstract
		Introduction
		Dataset Exploration
		Pre-Processing
		Models
		Results
		Conclusion and Discussion
		References
Index
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