Machine Learning
Choosing Regularization Parameters in Iterative Methods for Ill-Posed Problems
SIAM Journal on Matrix Analysis and Applications
Random Subwindows for Robust Image Classification
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Cross-Generalization: Learning Novel Classes from a Single Example by Feature Replacement
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Randomized Trees for Real-Time Keypoint Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
One-Shot Learning of Object Categories
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Sharing Visual Features for Multiclass and Multiview Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a meta-level prior for feature relevance from multiple related tasks
Proceedings of the 24th international conference on Machine learning
From Aardvark to Zorro: A Benchmark for Mammal Image Classification
International Journal of Computer Vision
Evaluating Color Descriptors for Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The human visual system is often able to learn to recognize difficult object categories from only a single view, whereas automatic object recognition with few training examples is still a challenging task. This is mainly due to the human ability to transfer knowledge from related classes. Therefore, an extension to Randomized Decision Trees is introduced for learning with very few examples by exploiting interclass relationships. The approach consists of a maximum a posteriori estimation of classifier parameters using a prior distribution learned from similar object categories. Experiments on binary and multiclass classification tasks show significant performance gains