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,...
For centuries, the deep connection between languages has brought about major discoveries about human communication. In this paper we investigate how this powerful source of inform...
We present a new unsupervised algorithm for training structured predictors that is discriminative, convex, and avoids the use of EM. The idea is to formulate an unsupervised versi...
Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dal...
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to ...
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...