Deep learning for image processing applications / edited by D. Jude Hemanth and Vania Vieira Estrela.

Format:

Book

Series:

Advances in parallel computing. 0927-5452 ; Volume 31.

Advances in parallel computing ; Volume 31

Language:

English

Subjects (All):

Image processing--Digital techniques.

Image processing.

Physical Description:

1 online resource (284 pages).

Edition:

1st ed.

Place of Publication:

Amsterdam ; Berlin ; Washington, DC : IOS Press, [2017]

Summary:

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.

Contents:

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 &amp

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.

Notes:

Description based on print version record.

Description based on publisher supplied metadata and other sources.

ISBN:

1-61499-822-1

OCLC:

1031468771