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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:
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.
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Title: Recent Advances in Logo Detection Using ...
Publisher: Springer
Publication Date: 2025
Binding: Soft cover
Condition: New
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Taschenbuch. Condition: Neu. Recent Advances in Logo Detection Using Machine Learning Paradigms | Theory and Practice | Yen-Wei Chen (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xii | Englisch | 2025 | Springer | EAN 9783031598135 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 133788730
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 132 pp. Englisch. Seller Inventory # 9783031598135
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 132 pp. Englisch. Seller Inventory # 9783031598135
Seller: Biblios, Frankfurt am main, HESSE, Germany
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