Genetic Programming for Image Classification: An Automated Approach to Feature Learning: 24 (Adaptation, Learning, and Optimization) - Tapa blanda

Bi, Ying; Xue, Bing; Zhang, Mengjie

 
9783030659295: Genetic Programming for Image Classification: An Automated Approach to Feature Learning: 24 (Adaptation, Learning, and Optimization)
Tapa blanda
ISBN 10: 3030659291 ISBN 13: 9783030659295
Editorial: Springer, 2022

Sinopsis

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.   

 


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Acerca del autor

Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.

De la contraportada

<p>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.&nbsp; &nbsp;</p><p>&nbsp;</p><br>

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Editorial
Springer
Año de publicación
2022
Idioma
Inglés
ISBN 10 
3030659291
ISBN 13 
9783030659295
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
288
Contacto del fabricante
no disponible
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Otras ediciones populares con el mismo título

9783030659264: Genetic Programming for Image Classification: An Automated Approach to Feature Learning: 24 (Adaptation, Learning, and Optimization)

Edición Destacada

ISBN 10:  3030659267 ISBN 13:  9783030659264
Editorial: Springer, 2021
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