Abstract
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 dataset and a comparison with K-nearest neighbour has shown the effectiveness and robustness of the proposed method.
Original language | English |
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Title of host publication | 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | IEEE International Conference on Fuzzy Systems 2012 - Brisbane, Australia Duration: 10 Jun 2012 → 15 Jun 2012 Conference number: 21st https://ieeexplore.ieee.org/xpl/conhome/6241469/proceeding (Proceedings) |
Publication series
Name | IEEE International Conference on Fuzzy Systems |
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ISSN (Print) | 1098-7584 |
Conference
Conference | IEEE International Conference on Fuzzy Systems 2012 |
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Abbreviated title | FUZZ-IEEE 2012 |
Country/Territory | Australia |
City | Brisbane |
Period | 10/06/12 → 15/06/12 |
Internet address |