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Multi-resolution-based road state estimation
Sun, Li1; Tang, Yuan Yan1; Wu, Tao2
2017-03-06
Conference Name2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016
Source PublicationProceedings - International Conference on Machine Learning and Cybernetics
Volume2
Pages1037-1041
Conference Date10-13 July 2016
Conference PlaceJeju
CountrySouth Korea
Author of SourceIEEE Computer Society
PublisherIEEE
Abstract

In this paper, we suggest an accessible and effective approach to the urban road state estimation. The main technical contribution of the proposed method is a novel feature extraction on the basis of the multi-resolution, along with support vector machine for classification. Experimental tests have been carried out to validate our proposed approach which can estimate road state in the sample of a hundred of city road images computational efficiently and effectively.

KeywordRoad State Estimation Multi-resolution Support Vector Machine
DOIhttps://doi.org/10.1109/ICMLC.2016.7873022
Indexed By其他
Language英语
Fulltext Access
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.University of Macau, China;
2.National University of Defense Technology, Changsha, P.R. China, 410073
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Sun, Li,Tang, Yuan Yan,Wu, Tao. Multi-resolution-based road state estimation[C]//IEEE Computer Society:IEEE,2017:1037-1041.
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