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» A Structural Framework for Assembly Modeling and Recognition
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ICDAR
2009
IEEE
14 years 3 months ago
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Xuefeng Chen, Xiabi Liu, Yunde Jia
ICASSP
2011
IEEE
13 years 9 days ago
Enriching Mandarin speech recognition by incorporating a hierarchical prosody model
This paper presents a new probabilistic framework of Mandarin speech recognition by incorporating a sophisticated hierarchical prosody model into the conventional HMM-based system...
Jyh-Her Yang, Ming-Chieh Liu, Hao-Hsiang Chang, Ch...
CVPR
2010
IEEE
14 years 4 months ago
Automatic Discovery of Meaningful Object Parts with Latent CRFs
Object recognition is challenging due to high intra-class variability caused, e.g., by articulation, viewpoint changes, and partial occlusion. Successful methods need to strike a...
Paul Schnitzspan, Stefan Roth, Bernt Schiele
COLING
2002
13 years 8 months ago
An Agent-based Approach to Chinese Named Entity Recognition
Chinese NE (Named Entity) recognition is a difficult problem because of the uncertainty in word segmentation and flexibility in language structure. This paper proposes the use of ...
Shiren Ye, Tat-Seng Chua, Jimin Liu
CVPR
2012
IEEE
11 years 11 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller