Stathopoulos, V. and Jose, J.M. (2011) Bayesian probabilistic models for image retrieval. Journal of Machine Learning Research: Workshop and Conference Proceedings, 17, pp. 41-47.
Full text not currently available from Enlighten.
Publisher's URL: http://proceedings.mlr.press/v17/stathopoulos11a.html
Abstract
In this paper we present new probabilistic ranking functions for content based image re- trieval. Our methodology generalises previous approaches and is based on the predictive densities of generative probabilistic models modelling the density of image features. We evaluate the proposed methodology and compare it against two state of the art image retrieval systems using a well known image collection.
| Item Type: | Articles |
|---|---|
| Additional Information: | Paper presented at the 2nd Workshop on Applications of Pattern Analysis, 19-21 Oct 2011, CIEM, Castro Urdiales, Spain |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Jose, Professor Joemon and Stathopoulos, Mr Vasileios |
| Authors: | Stathopoulos, V., and Jose, J.M. |
| Subjects: | Q Science > Q Science (General) |
| College/School: | College of Science and Engineering > School of Computing Science |
| Journal Name: | Journal of Machine Learning Research: Workshop and Conference Proceedings |
| ISSN: | 1938-7228 |
University Staff: Request a correction | Enlighten Editors: Update this record
Deposit and Record Details
Deposit and Record Details