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Once the vehicles are detected, a feature extraction method obtains the most significant features of this detected vehicles. When the extraction process is done, the vehicle types are determined by employing a set of Growing Neural Gas neural networks. The performance of the proposal has been analyzed from a qualitative and quantitative point of view by using a set of benchmark traffic video sequences, with acceptable results.<\/p>","DOI":"10.4018\/ijcvip.2017070101","type":"journal-article","created":{"date-parts":[[2017,8,28]],"date-time":"2017-08-28T08:08:59Z","timestamp":1503907739000},"page":"1-12","source":"Crossref","is-referenced-by-count":1,"title":["A Growing Neural Gas Approach to Classify Vehicles in Traffic Environments"],"prefix":"10.4018","volume":"7","author":[{"given":"Miguel A.","family":"Molina-Cabello","sequence":"first","affiliation":[{"name":"Department of Computer Languages and Computer Science. 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