dc.contributor.author | Madden, Michael G. | en |
dc.contributor.author | Munroe, Daniel T. | en |
dc.date.accessioned | 2009-05-15T10:16:29Z | en |
dc.date.available | 2009-05-15T10:16:29Z | en |
dc.date.issued | 2005 | en |
dc.identifier.citation | "Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images", Daniel Munroe and Michael G. Madden. Proceedings of AICS-05: Irish Conference on Artificial Intelligence and Cognitive Science, Portstewart, Sept 2005. | en |
dc.identifier.uri | http://hdl.handle.net/10379/191 | en |
dc.description.abstract | This paper investigates the use of machine learning classification techniques applied to the task of recognising the make and model of vehicles. Although a number of vehicle classification systems already exist, most of them seek only to distinguish between vehicle categories, e.g. identifying whether a vehicle is a bus, truck or car. The system presented here demonstrates that a set of features extracted from the frontal view of a vehicle may be used to determine the vehicle type (make and model) with high accuracy. The performance of some standard multi-class classification algorithms is compared for this problem. A one-class k-Nearest Neighbour classification algorithm is also implemented and tested. | en |
dc.format | application/pdf | en |
dc.language.iso | en | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.subject | Machine learning classification techniques | en |
dc.subject | Vehicle classification systems | en |
dc.subject | Classification algorithms | en |
dc.subject.lcsh | Machine learning | en |
dc.subject.lcsh | Algorithms | en |
dc.title | Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images | en |
dc.type | Conference Paper | en |
nui.item.downloads | 726 | |