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...
We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
In this paper we present a writer-dependent handwriting recognition system based on hidden Markov models (HMMs). This system, which has been developed in the context of research o...
This paper presents Domain Relevance Estimation (DRE), a fully unsupervised text categorization technique based on the statistical estimation of the relevance of a text with respe...
The goal of this work was to explore the optimization of the feature extraction module (front-end) parameters to improve bird species recognition. We explored optimizing the spect...
Martin Graciarena, Michelle Delplanche, Elizabeth ...