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» Hidden Conditional Random Fields for Meeting Segmentation
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ECCV
2010
Springer
15 years 3 months ago
What, Where & How Many? Combining Object Detectors and CRFs
Abstract. Computer vision algorithms for individual tasks such as object recognition, detection and segmentation have shown impressive results in the recent past. The next challeng...
ICASSP
2010
IEEE
14 years 10 months ago
Discriminative template extraction for direct modeling
This paper addresses the problem of developing appropriate features for use in direct modeling approaches to speech recognition, such as those based on Maximum Entropy models or S...
Shankar Shivappa, Patrick Nguyen, Geoffrey Zweig
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
15 years 10 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ICDAR
2007
IEEE
15 years 4 months ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
ECCV
2006
Springer
16 years 7 days ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...