Recent Advances in Logo Detection Using Machine Learning Paradigms (Hardcover)
Language: English
Published by Springer International Publishing AG, Cham, 2024
- Hardcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
£ 178.92
Quantity: 1 available
Add to basketItem description from seller
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
- Title
- Recent Advances in Logo Detection Using Machine Learning Paradigms (Hardcover)
- Author
- Yen-Wei Chen
- Publisher
- Springer International Publishing AG, Cham
- Publication year
- 2024
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3031598105
- ISBN 13
- 9783031598104
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
"About the title" may belong to another edition of this title.
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