Recent Advances in Logo Detection Using Machine Learning Paradigms: Theory and Practice: 255 (Intelligent Systems Reference Library, 255) - Hardcover
Synopsis
This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.
This book provides numerous ways that deep learners can use for logo recognition, including:
- Deep learning-based end-to-end trainable architecture for logo detection
- Weakly supervised logo recognition approach using attention mechanisms
- Anchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world images
- Unsupervised logo detection that takes into account domain-shift issues from synthetic to real-world images
- Approach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.
The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.
The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks.
"synopsis" may belong to another edition of this title.
About the Author
From the Back Cover
This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.
This book provides numerous ways that deep learners can use for logo recognition, including:
- Deep learning-based end-to-end trainable architecture for logo detection
- Weakly supervised logo recognition approach using attention mechanisms
- Anchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world images
- Unsupervised logo detection that takes into account domain-shift issues from synthetic to real-world images
- Approach for logo detection modelingdomain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.
The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.
The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks.
"About this title" may belong to another edition of this title.
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Recent Advances in Logo Detection using Machine Learning Paradigms
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ISBN 10: 3031598105
ISBN 13: 9783031598104
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes re. Seller Inventory # 1571794370
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Recent Advances in Logo Detection Using Machine Learning Paradigms
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including:Deep learning-based end-to-end trainable architecture for logo detectionWeakly supervised logo recognition approach using attention mechanismsAnchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world imagesUnsupervised logo detection that takes into account domain-shift issues from synthetic to real-world imagesApproach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks. 132 pp. Englisch. Seller Inventory # 9783031598104
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Recent Advances in Logo Detection Using Machine Learning Paradigms (Hardcover)
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Hardcover. Condition: new. Hardcover. This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including:Deep learning-based end-to-end trainable architecture for logo detectionWeakly supervised logo recognition approach using attention mechanismsAnchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world imagesUnsupervised logo detection that takes into account domain-shift issues from synthetic to real-world imagesApproach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783031598104
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Recent Advances in Logo Detection Using Machine Learning Paradigms: Theory and Practice (Intelligent Systems Reference Library, 255)
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Recent Advances in Logo Detection Using Machine Learning Paradigms | Theory and Practice
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Buch. Condition: Neu. Recent Advances in Logo Detection Using Machine Learning Paradigms | Theory and Practice | Yen-Wei Chen (u. a.) | Buch | xii | Englisch | 2024 | Springer | EAN 9783031598104 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 128860636
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Recent Advances in Logo Detection Using Machine Learning Paradigms
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ISBN 10: 3031598105
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Buch. Condition: Neu. Neuware -This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including:Deep learning-based end-to-end trainable architecture for logo detectionWeakly supervised logo recognition approach using attention mechanismsAnchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world imagesUnsupervised logo detection that takes into account domain-shift issues from synthetic to real-world imagesApproach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 132 pp. Englisch. Seller Inventory # 9783031598104
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Recent Advances in Logo Detection Using Machine Learning Paradigms : Theory and Practice
Published by
Springer International Publishing, Springer Nature Switzerland, 2024
ISBN 10: 3031598105
ISBN 13: 9783031598104
New
Hardcover
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including:Deep learning-based end-to-end trainable architecture for logo detectionWeakly supervised logo recognition approach using attention mechanismsAnchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world imagesUnsupervised logo detection that takes into account domain-shift issues from synthetic to real-world imagesApproach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks. Seller Inventory # 9783031598104
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Recent Advances in Logo Detection Using Machine Learning Paradigms: Theory and Practice (Intelligent Systems Reference Library, 255)
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