Semi-automatic annotation samples for vehicle type classification in urban environments

Chen, Z. and Ellis, T. J. (2015) Semi-automatic annotation samples for vehicle type classification in urban environments. IET Intelligent Transport Systems, 9(3), pp. 240-249. ISSN (print) 1751-956X

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Item Type: Article
Uncontrolled Keywords: closed circuit television, image classification, pattern clustering, road vehicles, support vector machines, traffic engineering computing, unsupervised learning, video cameras, semiautomatic annotation samples, vehicle type classification, urban environments, data collection, data annotation, classifier training, performance evaluation, roadside cctv video cameras, automatic image analysis, vehicle observation vector, unsupervised k-means clustering, iterative process, linear support vector machines classifier, annotated dataset
Research Area: Computer science and informatics
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing (until 2017)
Faculty of Science, Engineering and Computing (until 2017) > School of Computing and Information Systems
Depositing User: Automatic Import Agent
Date Deposited: 20 Jan 2015 09:12
Last Modified: 05 May 2015 10:28
DOI: https://doi.org/10.1049/iet-its.2013.0150
URI: http://eprints.kingston.ac.uk/id/eprint/29937

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