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In the literature, image-based target recognition has been extensively investigated in many use cases, such as facial recognition, but less so in the field of vehicle attribute recognition. We survey a number of algorithms that identify vehicle properties ranging from coarse-grained level (vehicle type) to fine-grained level (vehicle make and model). Moreover, we discuss two alternative approaches for these tasks, including straightforward classification and a more flexible metric learning method. Furthermore, we design a simulated real-world scenario for vehicle attribute recognition and present an experimental comparison of the two approaches.<\/jats:p>","DOI":"10.1007\/s11265-020-01567-6","type":"journal-article","created":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T02:02:31Z","timestamp":1593136951000},"page":"357-368","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification"],"prefix":"10.1007","volume":"93","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6438-5179","authenticated-orcid":false,"given":"Xingyang","family":"Ni","sequence":"first","affiliation":[]},{"given":"Heikki","family":"Huttunen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,6,26]]},"reference":[{"issue":"8","key":"1567_CR1","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1016\/j.imavis.2008.10.012","volume":"27","author":"V Abolghasemi","year":"2009","unstructured":"Abolghasemi, V., & Ahmadyfard, A. 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