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» Learning Structured Models for Phone Recognition
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ACCV
2006
Springer
14 years 23 days ago
Probabilistic Modeling for Structural Change Inference
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
Wei Liu, Véronique Prinet
CVPR
2012
IEEE
11 years 9 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
MCS
2009
Springer
14 years 1 months ago
A Study of Semi-supervised Generative Ensembles
Machine Learning can be divided into two schools of thought: generative model learning and discriminative model learning. While the MCS community has been focused mainly on the lat...
Manuela Zanda, Gavin Brown
CVPR
2008
IEEE
14 years 8 months ago
Hybrid body representation for integrated pose recognition, localization and segmentation
We propose a hybrid body representation that represents each typical pose by both template-like view information and part-based structural information. Specifically, each body par...
Cheng Chen, Guoliang Fan
CVPR
2009
IEEE
15 years 2 months ago
Understanding Videos, Constructing Plots - Learning a Visually Grounded Storyline Model from Annotated Videos
Analyzing videos of human activities involves not only recognizing actions (typically based on their appearances), but also determining the story/plot of the video. The storyline...
Abhinav Gupta (University of Maryland), Praveen Sr...