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ICML
2001
IEEE
14 years 8 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
ISMIR
2004
Springer
113views Music» more  ISMIR 2004»
14 years 1 months ago
Audio Features for Noisy Sound Segmentation
Automatic audio classification usually considers sounds as music, speech, silence or noise, but works about the noise class are rare. Audio features are generally specific to sp...
Pierre Hanna, Nicolas Louis, Myriam Desainte-Cathe...
SCVMA
2004
Springer
14 years 1 months ago
On the Relationship Between Image and Motion Segmentation
Abstract. In this paper we present a generative model for image sequences, which can be applied to motion segmentation and tracking, and to image sequence compression. The model co...
Adrian Barbu, Song Chun Zhu
ICIP
2004
IEEE
14 years 9 months ago
Stochastic modeling of volume images with a 3-d hidden markov model
Over the years, researchers in the image analysis community have successfully used various statistical modeling methods to segment, classify, and annotate digital images. In this ...
Jia Li, Dhiraj Joshi, James Ze Wang
ISCAS
2003
IEEE
108views Hardware» more  ISCAS 2003»
14 years 29 days ago
View-dependent transmission of 3-D normal meshes
—A unified approach to rate-distortion (R-D) optimized compression and view-dependent transmission of three-dimensional (3-D) normal meshes is investigated in this work. A norma...
Jae-Young Sim, Chang-Su Kim, C. C. Jay Kuo, Sang U...