| 书目名称 | Recent Advances in Logo Detection Using Machine Learning Paradigms |
| 副标题 | Theory and Practice |
| 编辑 | Yen-Wei Chen,Xiang Ruan,Rahul Kumar Jain |
| 视频video | |
| 概述 | Presents the novel logo detection methods using machine learning paradigms.Demonstrates the merits of the presented approaches over the reported approaches using the real-world applications. Includes |
| 丛书名称 | Intelligent Systems Reference Library |
| 图书封面 |  |
| 描述 | .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 analys |
| 出版日期 | Book 2024 |
| 关键词 | Intelligent Systems; Deep Learning; Anchorless/Anchorfree Object Detectors; Feature Extraction; Attentio |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-59811-1 |
| isbn_softcover | 978-3-031-59813-5 |
| isbn_ebook | 978-3-031-59811-1Series ISSN 1868-4394 Series E-ISSN 1868-4408 |
| issn_series | 1868-4394 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 16:59:21
