Support vector domain description
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
A region—based image database system using colour and texture
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Shrinking the tube: a new support vector regression algorithm
Proceedings of the 1998 conference on Advances in neural information processing systems II
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Pattern Recognition Methods in Image and Video Databases: Past, Present and Future
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
A Discussion on the Classifier Projection Space for Classifier Combining
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Weakly Supervised Learning of Visual Models and Its Application to Content-Based Retrieval
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Dynamic pattern denoising method using multi-basin system with kernels
Pattern Recognition
One-class classification with gaussian processes
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
One-class classification with Gaussian processes
Pattern Recognition
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In image retrieval systems, images can be represented by single feature vectors or by clouds of points. A cloud of points offers a more flexible description but suffers from class overlap. We propose a novel approach for describing clouds of points based on support vector data description (SVDD). We show that combining SVDD-based classifiers improves the retrieval precision. We investigate the performance of the proposed retrieval technique on a database of 368 texture images and compare it to other methods.