Handbook of Research on Deep Learning Innovations and Trends
- 7h 13m
- Aboul Ella Hassanien, Ashraf Darwish, Chiranji Lal Chowdhary (eds)
- IGI Global
- 2019
Leading technology firms and research institutions are continuously exploring new techniques in artificial intelligence and machine learning. As such, deep learning has now been recognized in various real-world applications such as computer vision, image processing, biometrics, pattern recognition, and medical imaging. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient.
The Handbook of Research on Deep Learning Innovations and Trends is an essential scholarly resource that presents current trends and the latest research on deep learning and explores the concepts, algorithms, and techniques of data mining and analysis. Highlighting topics such as computer vision, encryption systems, and biometrics, this book is ideal for researchers, practitioners, industry professionals, students, and academicians.
In this Book
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Detection of Blood-Related Diseases Using Deep Neural Nets
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Enhanced Footsteps Generation Method for Walking Robots Based on Convolutional Neural Networks
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CNN Customizations with Transfer Learning for Face Recognition Task
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Application of Deep Learning in Speech Recognition
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Sensation of Deep Learning in Image Processing Applications
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Transfer Learning in 2.5D Face Image for Occlusion Presence and Gender Classification
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Deep Learning: Architectures and Applications
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A Survey on Deep Learning Techniques Used for Quality Process
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Deep Learning in Early Detection of Alzheimer's: A Study
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Deep Clustering
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Deep Reinforcement Learning for Optimization
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A Similarity-Based Object Classification Using Deep Neural Networks
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Cognitive Deep Learning: Future Direction in Intelligent Retrieval
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Malware Classification and Analysis Using Convolutional and Recurrent Neural Network
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Anomaly Detection Using Deep Learning with Modular Networks
