Téléchargez le livre : Genetic Programming for Image Classification

Genetic Programming for Image Classification

An Automated Approach to Feature Learning de

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Éditeur :

Springer


Collection :

Adaptation, Learning, and Optimization

Paru le : 2021-02-08

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Description


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 andpostgraduate level textbook in artificial intelligence, machine learning, computer vision, and evolutionary computation.   
 
Pages
258 pages
Collection
Adaptation, Learning, and Optimization
Parution
2021-02-08
Marque
Springer
EAN papier
9783030659264
EAN PDF
9783030659271
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
10947 Ko
Prix
147,69 €
EAN EPUB
9783030659271
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
38339 Ko
Prix
147,69 €

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