Genetic programming for image classification : an automated approach to feature learning / Ying Bi, Bing Xue, Mengjie Zhang.
2021
QA76.623
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Details
Title
Genetic programming for image classification : an automated approach to feature learning / Ying Bi, Bing Xue, Mengjie Zhang.
Author
Bi, Ying, author.
ISBN
9783030659271 (electronic bk.)
3030659275 (electronic bk.)
3030659267
9783030659264
3030659275 (electronic bk.)
3030659267
9783030659264
Published
Cham : Springer, [2021]
Language
English
Description
1 online resource (279 pages)
Item Number
10.1007/978-3-030-65927-1 doi
Call Number
QA76.623
Dewey Decimal Classification
006.3/1
Summary
This book offers several new GP approaches to feature learning for image classification. Image classification is an important task in computer vision and machine learning with a wide range of applications. Feature learning is a fundamental step in image classification, but it is difficult due to the high variations of images. Genetic Programming (GP) is an evolutionary computation technique that can automatically evolve computer programs to solve any given problem. This is an important research field of GP and image classification. No book has been published in this field. This book shows how different techniques, e.g., image operators, ensembles, and surrogate, are proposed and employed to improve the accuracy and/or computational efficiency of GP for image classification. The proposed methods are applied to many different image classification tasks, and the effectiveness and interpretability of the learned models will be demonstrated. This book is suitable as a graduate and postgraduate level textbook in artificial intelligence, machine learning, computer vision, and evolutionary computation.
Bibliography, etc. Note
Includes bibliographical references and index.
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text file
PDF
Source of Description
Description based on print version record.
Series
Adaptation, learning and optimization ; v. 24.
Available in Other Form
Genetic Programming for Image Classification.
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Online Access
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Table of Contents
Computer Vision and Machine Learning
Evolutionary Computation and Genetic Programming
Multi-Layer Representation for Binary Image Classification
Evolutionary Deep Learning Using GP with Convolution Operators
GP with Image Descriptors for Learning Global and Local Features
GP with Image-Related Operators for Feature Learning
GP for Simultaneous Feature Learning and Ensemble Learning
Random Forest-Assisted GP for Feature Learning
Conclusions and Future Directions.
Evolutionary Computation and Genetic Programming
Multi-Layer Representation for Binary Image Classification
Evolutionary Deep Learning Using GP with Convolution Operators
GP with Image Descriptors for Learning Global and Local Features
GP with Image-Related Operators for Feature Learning
GP for Simultaneous Feature Learning and Ensemble Learning
Random Forest-Assisted GP for Feature Learning
Conclusions and Future Directions.