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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| Main Authors: | , |
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| 格式: | Conference or Workshop Item |
| 語言: | English |
| 出版: |
2012
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| 主題: | |
| 在線閱讀: | http://eprints.um.edu.my/14091/1/426.pdf http://eprints.um.edu.my/14091/ |
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| 總結: | 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.
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