The image processing handbook
The nature of statistical learning theory
The nature of statistical learning theory
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
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ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
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WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Automatic Detection of Intestinal Juices in Wireless Capsule Video Endoscopy
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Co-training for predicting emotions with spoken dialogue data
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
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This work tackles the problem of learning a robust classification function from a very small sample set when a related but unlabeled data set is provided. To this end we define a new semi-supervised method that is based on a stability criterion. We successfully apply our proposal in the specific case of automatic diagnosis of intestinal motility disease using video capsule endoscopy. An experimental evaluation shows the viability to apply the proposed method in motility disfunction diagnosis.