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SIGIR
2003
ACM
15 years 5 months ago
Table extraction using conditional random fields
The ability to find tables and extract information from them is a necessary component of data mining, question answering, and other information retrieval tasks. Documents often c...
David Pinto, Andrew McCallum, Xing Wei, W. Bruce C...
ISBI
2008
IEEE
15 years 7 months ago
Support vector driven Markov random fields towards DTI segmentation of the human skeletal muscle
In this paper we propose a classification-based method towards the segmentation of diffusion tensor images. We use Support Vector Machines to classify diffusion tensors and we ex...
Radhouène Neji, Gilles Fleury, Jean Francoi...
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ICCV
2007
IEEE
15 years 7 months ago
Real-Time Automatic Kinematic Model Building for Optical Motion Capture Using a Markov Random Field
Abstract. We present a completely autonomous algorithm for the real-time creation of a moving subject’s kinematic model from optical motion capture data and with no a priori info...
Stjepan Rajko, Gang Qian
ICIP
2007
IEEE
15 years 7 months ago
Lossy Compression of Bilevel Images Based on Markov Random Fields
A new method for lossy compression of bilevel images based on Markov random fields (MRFs) is proposed. It preserves key structural information about the image, and then reconstru...
Matthew G. Reyes, Xiaonan Zhao, David L. Neuhoff, ...
ICPR
2006
IEEE
15 years 6 months ago
A Conditional Random Field Model for Video Super-resolution
In this paper, we propose a learning-based method for video super-resolution. There are two main contributions of the proposed method. First, information from cameras with differe...
Dan Kong, Mei Han, Wei Xu, Hai Tao, Yihong Gong