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» Training Deformable Models for Localization
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NAACL
2010
13 years 6 months ago
Painless Unsupervised Learning with Features
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
ICANN
2005
Springer
14 years 1 months ago
Accurate and Robust Image Superresolution by Neural Processing of Local Image Representations
Image superresolution involves the processing of an image sequence to generate a still image with higher resolution. Classical approaches, such as bayesian MAP methods, require ite...
Carlos Miravet, Francisco de Borja Rodrígue...
ICASSP
2010
IEEE
13 years 8 months ago
HMM-based separation of acoustic transfer function for single-channel sound source localization
This paper presents a sound source (talker) localization method using only a single microphone, where a HMM (Hidden Markov Model) of clean speech is introduced to estimate the aco...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
MOBICOM
2004
ACM
14 years 1 months ago
Practical robust localization over large-scale 802.11 wireless networks
We demonstrate a system built using probabilistic techniques that allows for remarkably accurate localization across our entire office building using nothing more than the built-...
Andreas Haeberlen, Eliot Flannery, Andrew M. Ladd,...
EMMCVPR
2001
Springer
14 years 23 days ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade