Recent Advances in Logo Detection Using Machine Leaing Paradigms:Theory and Practice (Intelligent Systems Reference Library, 255)

by: Yen-Wei Chen (Author),Xiang Ruan(Author),Rahul Kumar Jain(Author)&0more

Publisher: Springer

Edition: 2024th

Publication Date: 2024/5/31

Language: English

Print Length: 131 pages

ISBN-10: 3031598105

ISBN-13: 9783031598104

Book Description

This book presents the current trends in deep leaing-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 leaing. 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 leaers can use for logo recognition, including:Deep leaing-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 leaing 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 leaing 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 leaing techniques and applications in logo and various object detection tasks.

About the Author

This book presents the current trends in deep leaing-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 leaing. 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 leaers can use for logo recognition, including:Deep leaing-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 leaing 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 leaing 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 leaing techniques and applications in logo and various object detection tasks.

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