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17 years 3 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
147
Voted
MLMI
2004
Springer
15 years 10 months ago
Mapping from Speech to Images Using Continuous State Space Models
In this paper a system that transforms speech waveforms to animated faces are proposed. The system relies on continuous state space models to perform the mapping, this makes it po...
Tue Lehn-Schiøler, Lars Kai Hansen, Jan Lar...
EMNLP
2004
15 years 6 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...
SAC
2003
ACM
15 years 10 months ago
A Markov Random Field Model of Microarray Gridding
DNA microarray hybridisation is a popular high throughput technique in academic as well as industrial functional genomics research. In this paper we present a new approach to auto...
Mathias Katzer, Franz Kummert, Gerhard Sagerer
CVPR
2010
IEEE
15 years 9 months ago
A Novel Markov Random Field Based Deformable Model for Face Recognition
In this paper, a new scheme to address the face recognition problem is proposed. Different from traditional face recognition approaches which represent each facial image by a sing...
Shu Liao, Albert C.S. Chung