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JMLR
2010
202views more  JMLR 2010»
13 years 2 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
CIVR
2007
Springer
241views Image Analysis» more  CIVR 2007»
14 years 1 months ago
A robust scene recognition system for baseball broadcast using data-driven approach
We propose a robust scene recognition system for baseball broadcast videos. This system is based on the data-driven approach which has been successful in continuous speech recogni...
Ryoichi Ando, Koichi Shinoda, Sadaoki Furui, Takah...
ICIP
2008
IEEE
14 years 9 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
ICPR
2008
IEEE
14 years 8 months ago
Automatic generation of HMM topology for sign language recognition
Sign language is used for communicating to people with hearing difficulties. Recogntion of a sign language image sequence is challenging because of the variety of hand shapes and ...
Tadashi Matsuo, Yoshiaki Shirai, Nobutaka Shimada
CVPR
2004
IEEE
14 years 9 months ago
A Unified Spatio-Temporal Articulated Model for Tracking
Tracking articulated objects in image sequences remains a challenging problem, particularly in terms of the ability to localize the individual parts of an object given selfocclusi...
Xiangyang Lan, Daniel P. Huttenlocher