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JMLR
2010
202views more  JMLR 2010»
14 years 4 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»
15 years 3 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
15 years 11 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
15 years 10 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
15 years 11 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