This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artifacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
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This book
- Provides a concise and structured presentation of deep learning applications
- Introduces a large range of applications related to vision, speech, and natural language processing
- Includes active research trends, challenges, and future directions of deep learning
- This book presents a broad range of deep-learning applications
Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times.Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
Content
- Designing a Neural Network from Scratch for Big Data Powered by Multi-node GPUs
- Deep Learning for Scene Understanding
- An Application of Deep Learning in Character Recognition: An Overview
- Deep Learning for Driverless Vehicles
- Deep Learning for Document Representation
- Applications of Deep Learning in Medical Imaging
- Deep Learning for Marine Species Recognition
- Deep Molecular Representation in Cheminformatics
- A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving
- Phase Identification and Workflow Modeling in Laparoscopy Surgeries Using Temporal Connectionism of Deep Visual Residual Abstractions
- Deep Learning Applications to Cytopathology: A Study on the Detection of Malaria and on the Classification of Leukaemia Cell-Lines
- Application of Deep Neural Networks for Disease Diagnosis Through Medical Data Sets
- Why Dose Layer-by-Layer Pre-training Improve Deep Neural Networks Learning?
- Deep Learning in eHealth
- Deep Learning for Brain Computer Interfaces
- Reducing Hierarchical Deep Learning Networks as Game Playing Artefact Using Regret Matching
- Deep Learning in Gene Expression Modeling
About the author:
Sanjiban Sekhar Roy is an Associate Professor in the School of Computer Science and Engineering, Vellore Institute of Technology(VIT), India. He joined VIT in the year of 2009 as an Asst. Professor. Prior to joining VIT University Sanjiban had nine months of research experience in Dept. Computer Sc and Eng, Indian Institute of Technology(IIT) Kharagpur. His research interests include Deep Learning and AI. He has published around 45 articles in international journals and conferences. He also is editorial board members of international journals. Besides, he has edited four books with reputed international publishers like Elsevier, Springer and IGI Global.
Below links will give you more idea about his work. You can contact him through linked in.
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