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Intelligent Systems Reference Library255- Recent Advances in Logo Detection Using Machine Learning Paradigms Theory and Practice

Intelligent Systems Reference Library255- Recent Advances in Logo Detection Using Machine Learning Paradigms Theory and Practice

Le prix initial était : 155.00 €.Le prix actuel est : 31.00 €.

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…

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Description

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.

Langue
en
Version
Couverture rigide
Date de sortie initiale
31 mai 2024
Nombre de pages
119
Illustrations
Avec illustrations

Personnes impliquées

Auteur principal

Yen-Wei Chen

Deuxième auteur

Xiang Ruan

Editeur principal

Springer International Publishing Ag

Informations sur le fabricant

Nom du fabricant
Springer Nature Customer Service Center GmbH
Adresse du fabricant
Europaplatz 3,69115 Heidelberg, Germany – 69115 – Heidelberg – DE
Adresse électronique du fabricant
ProductSafety@springernature.com

Autres spécifications

Hauteur de l’emballage
13 mm
Largeur d’emballage
155 mm
Largeur du produit
155 mm
Livre d‘étude
Non
Longueur d’emballage
235 mm
Longueur du produit
235 mm
Poids de l’emballage
395 g
Édition
2024

EAN

EAN
9783031598104

Sécurité des produits

Opérateur économique responsable dans l’UE

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Catégories

Ordinateurs et Informatique

Technologies informatiques

Bases de données

Intelligence artificielle

Livres

Livre, ebook ou livre audio ?

Livre

Disponibilité

Disponible à l’adresse suivante

Langue

Anglais

Type de livre

Hardcover

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