A fuzzy qualitative approach for scene classification
Scene classification has been studied extensively in the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even giv...
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2012
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| Online Access: | http://eprints.um.edu.my/14091/ http://eprints.um.edu.my/14091/1/426.pdf |
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um-14091 |
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eprints |
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um-140912015-09-22T00:06:03Z A fuzzy qualitative approach for scene classification Lim, C.H. Chan, C.S. T Technology (General) Scene classification has been studied extensively in the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even given a same scene image. In this paper, we propose a fuzzy qualitative approach to address this problem. That is, we first adopted the fuzzy quantity space to model the training data. Secondly, we present a novel weight function, w to train a fuzzy qualitative scene model in the fuzzy qualitative states. Finally, we introduce fuzzy qualitative partition to perform the scene classification. Empirical results using a standard data set and a comparison with K-nearest neighbour has shown the effectiveness and robustness of the proposed method. 2012-06 Conference or Workshop Item PeerReviewed application/pdf http://eprints.um.edu.my/14091/1/426.pdf Lim, C.H.; Chan, C.S. (2012) A fuzzy qualitative approach for scene classification. In: World Congress on Computational Intelligence , 10-15 June 2012, Brisbane, Australia. http://eprints.um.edu.my/14091/ |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
University Malaya |
| building |
UM Research Repository |
| collection |
Online Access |
| topic |
T Technology (General) |
| spellingShingle |
T Technology (General) Lim, C.H. Chan, C.S. A fuzzy qualitative approach for scene classification |
| description |
Scene classification has been studied extensively in
the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even given a same scene image. In this paper, we propose a fuzzy qualitative approach to address this problem. That is, we first adopted the fuzzy quantity space to model the training data. Secondly, we present a novel weight function, w to train a fuzzy qualitative scene model in the fuzzy qualitative states. Finally, we introduce
fuzzy qualitative partition to perform the scene classification. Empirical results using a standard data set and a comparison with K-nearest neighbour has shown the effectiveness and robustness of the proposed method.
|
| format |
Conference or Workshop Item |
| author |
Lim, C.H. Chan, C.S. |
| author_facet |
Lim, C.H. Chan, C.S. |
| author_sort |
Lim, C.H. |
| title |
A fuzzy qualitative approach for scene classification |
| title_short |
A fuzzy qualitative approach for scene classification |
| title_full |
A fuzzy qualitative approach for scene classification |
| title_fullStr |
A fuzzy qualitative approach for scene classification |
| title_full_unstemmed |
A fuzzy qualitative approach for scene classification |
| title_sort |
fuzzy qualitative approach for scene classification |
| publishDate |
2012 |
| url |
http://eprints.um.edu.my/14091/ http://eprints.um.edu.my/14091/1/426.pdf |
| first_indexed |
2018-09-06T06:20:12Z |
| last_indexed |
2018-09-06T06:20:12Z |
| _version_ |
1610837983151259648 |