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CVPR
2007
IEEE
16 years 9 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
ECCV
2008
Springer
16 years 9 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher
OSDI
2004
ACM
16 years 7 months ago
Energy-Efficiency and Storage Flexibility in the Blue File System
A fundamental vision driving pervasive computing research is access to personal and shared data anywhere at anytime. In many ways, this vision is close to being realized. Wireless...
Edmund B. Nightingale, Jason Flinn

Publication
443views
17 years 2 months ago
Luminance Distribution Control based on the Separation of Direct and Indirect Components
We propose a method to control the luminance distribution on a scene by modeling the light propagation with direct and indirect components separately. To reduce the measurement tim...
Osamu Nasu, Shinsaku Hiura, Kosuke Sato
ICML
2000
IEEE
16 years 8 months ago
Learning Bayesian Networks for Diverse and Varying numbers of Evidence Sets
We introduce an expandable Bayesian network (EBN) to handle the combination of diverse multiple homogeneous evidence sets. An EBN is an augmented Bayesian network which instantiat...
Zu Whan Kim, Ramakant Nevatia
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