
Deep Learning for Image Processing Applications
Description
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The aim of this book, 'Deep Learning for Image Processing Applications', is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data.
The book will be of interest to all those whose work involves the use of deep learning and image processing techniques.
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Content
- Title Page
- Preface
- Contents
- About the Editors
- Mind, Machine, and Image Processing
- Deep Neural Networks for Image Classification
- Virtual Robotic Arm Control with Hand Gesture Recognition and Deep Learning Strategies
- Intelligent Image Retrieval via Deep Learning Techniques
- Advanced Stevia Disease Detection Using Deep Learning
- Analysis of Tuberculosis Images Using Differential Evolutionary Extreme Learning Machines (DE-ELM)
- Object Retrieval with Deep Convolutional Features
- Hierarchical Object Detection with Deep Reinforcement Learning
- Big Data & Deep Data: Minding the Challenges
- Sparse-Filtered Convolutional Neural Networks with Layer-Skipping (SF-CNNLS) for Intra-Class Variation of Vehicle Type Recognition
- On the Prospects of Using Deep Learning for Surveillance and Security Applications
- Super-Resolution of Long Range Captured Iris Image Using Deep Convolutional Network
- Subject Index
- Author Index
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File format: PDF
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