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Deep Learning for Image Processing Applications [Pehme köide]

  • Formaat: Paperback / softback, 284 pages, kõrgus x laius x paksus: 234x156x15 mm, kaal: 399 g, Illustrations
  • Sari: Advances in Parallel Computing 31
  • Ilmumisaeg: 29-Apr-2025
  • Kirjastus: IOS Press,US
  • ISBN-10: 1614998213
  • ISBN-13: 9781614998211
Teised raamatud teemal:
  • Formaat: Paperback / softback, 284 pages, kõrgus x laius x paksus: 234x156x15 mm, kaal: 399 g, Illustrations
  • Sari: Advances in Parallel Computing 31
  • Ilmumisaeg: 29-Apr-2025
  • Kirjastus: IOS Press,US
  • ISBN-10: 1614998213
  • ISBN-13: 9781614998211
Teised raamatud teemal:
Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance.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.
Preface v
D. Jude Hemanth
Vania Viera Estrela
About the Editors vii
Mind, Machine, and Image Processing
1(26)
Subhash Chandra Pandey
Deep Neural Networks for Image Classification
27(23)
A. Vasuki
S. Govindaraju
Virtual Robotic Arm Control with Hand Gesture Recognition and Deep Learning Strategies
50(18)
K. Martin Sagayam
T. Vedha Viyas
Chiung Ching Ho
Lawrence E. Henesey
Intelligent Image Retrieval via Deep Learning Techniques
68(26)
Rajeev Kumar Singh
Suchitra Agrawal
Uday Pratap Singh
Sanjeev Jain
Advanced Stevia Disease Detection Using Deep Learning
94(17)
S. Lakshmi
R. Sivakumar
Analysis of Tuberculosis Images Using Differential Evolutionary Extreme Learning Machines (DE-ELM)
111(26)
E. Priya
S. Srinivasan
Object Retrieval with Deep Convolutional Features
137(27)
Eva Mohedano
Amaia Salvador
Kevin McGuinness
Xavier Giro-i-Nieto
Noel E. O'Connor
Ferran Marques
Hierarchical Object Detection with Deep Reinforcement Learning
164(13)
Miriam Bellver Bueno
Xavier Giro-i-Nieto
Ferran Marques
Jordi Torres
Big Data & Deep Data: Minding the Challenges
177(17)
Madhulika Bhatia
Mamta Mittal
Madhurima
Sparse-Filtered Convolutional Neural Networks with Layer-Skipping (SF-CNNLS) for Intra-Class Variation of Vehicle Type Recognition
194(24)
Suryanti Awang
Nik Mohamad Aizuddin Nik Azmi
On the Prospects of Using Deep Learning for Surveillance and Security Applications
218(26)
Shuo Liu
Vijay John
Zheng Liu
Super-Resolution of Long Range Captured Iris Image Using Deep Convolutional Network
244(27)
Anand Deshpande
Prashant P. Patavardhan
Subject Index 271(2)
Author Index 273