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» Hidden Maximum Entropy Approach for Visual Concept Modeling
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CVPR
2007
IEEE
15 years 27 days ago
Segmental Hidden Markov Models for View-based Sport Video Analysis
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Yi Ding, Guoliang Fan
EMNLP
2004
14 years 8 days 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...
PCM
2005
Springer
107views Multimedia» more  PCM 2005»
14 years 4 months ago
Salient Feature Selection for Visual Concept Learning
Abstract. Image classification could be treated as an effective solution to enable keyword-based semantic image retrieval. In this paper, we propose a novel image classification...
Feng Xu, Lei Zhang, Yu-Jin Zhang, Wei-Ying Ma
ECML
2005
Springer
14 years 4 months ago
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
PRL
2007
155views more  PRL 2007»
13 years 10 months ago
Integrated patch model: A generative model for image categorization based on feature selection
Image categorization could be treated as an effective solution to enable keyword-based image retrieval. In this paper, we propose a novel image categorization approach by learnin...
Feng Xu, Yu-Jin Zhang