Deep Hierarchical Representation from Classifying Logo-405

We introduce a logo classification mechanism which combines a series of deep representations obtained by fine-tuning convolutional neural network (CNN) architectures and traditional pattern recognition algorithms. In order to evaluate the proposed mechanism, we build a middle-scale logo dataset (nam...

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Main Authors: Sujuan Hou, Jianwei Lin, Shangbo Zhou, Maoling Qin, Weikuan Jia, Yuanjie Zheng
Format: Article
Language:English
Published: Hindawi-Wiley 2017-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2017/3169149
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author Sujuan Hou
Jianwei Lin
Shangbo Zhou
Maoling Qin
Weikuan Jia
Yuanjie Zheng
author_facet Sujuan Hou
Jianwei Lin
Shangbo Zhou
Maoling Qin
Weikuan Jia
Yuanjie Zheng
author_sort Sujuan Hou
collection DOAJ
description We introduce a logo classification mechanism which combines a series of deep representations obtained by fine-tuning convolutional neural network (CNN) architectures and traditional pattern recognition algorithms. In order to evaluate the proposed mechanism, we build a middle-scale logo dataset (named Logo-405) and treat it as a benchmark for logo related research. Our experiments are carried out on both the Logo-405 dataset and the publicly available FlickrLogos-32 dataset. The experimental results demonstrate that the proposed mechanism outperforms two popular ways used for logo classification, including the strategies that integrate hand-crafted features and traditional pattern recognition algorithms and the models which employ deep CNNs.
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spelling doaj.art-bd50167cd8c947a2a6415be9abe21b852022-12-22T03:57:54ZengHindawi-WileyComplexity1076-27871099-05262017-01-01201710.1155/2017/31691493169149Deep Hierarchical Representation from Classifying Logo-405Sujuan Hou0Jianwei Lin1Shangbo Zhou2Maoling Qin3Weikuan Jia4Yuanjie Zheng5School of Information Science and Engineering, Shandong Normal University, Jinan 250014, ChinaSchool of Information Science and Engineering, Shandong Normal University, Jinan 250014, ChinaSchool of Computer Science, Chongqing University, Chongqing 400030, ChinaSchool of Information Science and Engineering, Shandong Normal University, Jinan 250014, ChinaSchool of Information Science and Engineering, Shandong Normal University, Jinan 250014, ChinaSchool of Information Science and Engineering, Shandong Normal University, Jinan 250014, ChinaWe introduce a logo classification mechanism which combines a series of deep representations obtained by fine-tuning convolutional neural network (CNN) architectures and traditional pattern recognition algorithms. In order to evaluate the proposed mechanism, we build a middle-scale logo dataset (named Logo-405) and treat it as a benchmark for logo related research. Our experiments are carried out on both the Logo-405 dataset and the publicly available FlickrLogos-32 dataset. The experimental results demonstrate that the proposed mechanism outperforms two popular ways used for logo classification, including the strategies that integrate hand-crafted features and traditional pattern recognition algorithms and the models which employ deep CNNs.http://dx.doi.org/10.1155/2017/3169149
spellingShingle Sujuan Hou
Jianwei Lin
Shangbo Zhou
Maoling Qin
Weikuan Jia
Yuanjie Zheng
Deep Hierarchical Representation from Classifying Logo-405
Complexity
title Deep Hierarchical Representation from Classifying Logo-405
title_full Deep Hierarchical Representation from Classifying Logo-405
title_fullStr Deep Hierarchical Representation from Classifying Logo-405
title_full_unstemmed Deep Hierarchical Representation from Classifying Logo-405
title_short Deep Hierarchical Representation from Classifying Logo-405
title_sort deep hierarchical representation from classifying logo 405
url http://dx.doi.org/10.1155/2017/3169149
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AT jianweilin deephierarchicalrepresentationfromclassifyinglogo405
AT shangbozhou deephierarchicalrepresentationfromclassifyinglogo405
AT maolingqin deephierarchicalrepresentationfromclassifyinglogo405
AT weikuanjia deephierarchicalrepresentationfromclassifyinglogo405
AT yuanjiezheng deephierarchicalrepresentationfromclassifyinglogo405