Genetic Programming for Image Classification

- An Automated Approach to Feature Learning (2021)

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indgår i serie Adaptation, Learning, and Optimization


Genetic Programming for Image Classification
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Format:
Bog, hardback
Udgivelsesdato:
21-02-2021
Sprog:
Engelsk
Udgave:
1st ed. 2021.
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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.

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Udgivelsesdato:
21-02-2021
ISBN13:
9783030659264
Bredde:
155 mm
Højde:
235 mm
Forlag:
Springer
Nummer i serien:
24
Format:
Hardback
Forfattere
Bibliotekernes beskrivelse This book offers several new GP approaches to feature learning for image classification. 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. 1 Hardback X, 290 p.

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