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Ajouter au panierEtat : New.
Edité par Taylor & Francis Ltd, London, 2023
ISBN 10 : 1032181184 ISBN 13 : 9781032181189
Langue: anglais
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Ajouter au panierHardcover. Etat : new. Hardcover. Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning. Accurately detecting crack localization is not an easy task. This book addresses important issues in detecting crack-like objects and provides a practical smart pavement surface inspection system using deep learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Ajouter au panierEtat : New.
Edité par Taylor and Francis Ltd, GB, 2023
ISBN 10 : 1032181184 ISBN 13 : 9781032181189
Langue: anglais
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Ajouter au panierHardback. Etat : New. Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.
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Ajouter au panierHardback. Etat : New. New copy - Usually dispatched within 4 working days. 166.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Taylor and Francis Ltd, GB, 2023
ISBN 10 : 1032181184 ISBN 13 : 9781032181189
Langue: anglais
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Ajouter au panierHardback. Etat : New. Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.
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Edition originale
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Ajouter au panierEtat : New. 2023. 1st Edition. Hardcover. . . . . .
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Ajouter au panierEtat : New. 2023. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.
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Ajouter au panierHardcover. Etat : Brand New. 100 pages. 8.50x5.44x1.30 inches. In Stock.
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Ajouter au panierGebunden. Etat : New. Kaige Zhang has a B.S. degree (2011) in electronic engineering from the Harbin Institute of Technology, China, and a Ph.D. degree (2019) in computer science from Utah State University, USA. His research interests include computer vision,.