Overview
- Reviews exhaustively the key recent research into deep learning applications in image analysis
- Covers many different deep learning applications in medical, satellite, forensic image analysis
- Demonstrates the deep learning approach as effective solutions for various image-related problems
Part of the book series: Studies in Big Data (SBD, volume 129)
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About this book
The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.
Keywords
Table of contents (10 chapters)
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Deep Learning Applications in Image Analysis
Editors: Sanjiban Sekhar Roy, Ching-Hsien Hsu, Venkateshwara Kagita
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-981-99-3784-4
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-99-3783-7Published: 09 July 2023
Softcover ISBN: 978-981-99-3786-8Published: 10 July 2024
eBook ISBN: 978-981-99-3784-4Published: 08 July 2023
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XII, 210
Number of Illustrations: 26 b/w illustrations, 96 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Machine Learning