In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists...
Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau,...
In this paper, we investigate linear discriminant analysis (LDA) methods for multiclass classification problems in hyperspectral imaging. We note that LDA does not consider pairwi...
Courseware systems are often based on an assembly of different components, addressing the different needs of storage and delivery functionality. The Learning Technology Standard A...
For a large class of applications, there is time to train the system. In this paper, we propose a learning-based approach to patch perspective rectification, and show that it is b...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...