SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual Data
IEEE Transactions on Knowledge and Data Engineering
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
AutoAlbum: Clustering Digital Photographs using Probabilistic Model Merging
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Bayesian fusion of camera metadata cues in semantic scene classification
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
High dimensional problem based on elite-grouped adaptive particle swarm optimization
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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Image classification and clustering is a challenging problem in computer vision. This paper proposed a kind of particle swarm optimization clustering approach: FPSOC to process image clustering problem. This approach considers each particle as a candidate cluster center. The particles fly in the solution space to search suitable cluster centers. This method is different from previous work in that it employs fuzzy concept in particle swarm optimization clustering and adopts attribute selection mechanism to avoid the ‘curse of dimensionality’ problem. The experimental results show that the presented approach can properly process image clustering problem.