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» Experimental Analysis of BRDF Models
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ICDAR
2009
IEEE
15 years 11 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
NIPS
2007
15 years 5 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
ACL
2012
13 years 6 months ago
Aspect Extraction through Semi-Supervised Modeling
Aspect extraction is a central problem in sentiment analysis. Current methods either extract aspects without categorizing them, or extract and categorize them using unsupervised t...
Arjun Mukherjee, Bing Liu 0001
MIR
2006
ACM
220views Multimedia» more  MIR 2006»
15 years 10 months ago
Robust scene recognition using language models for scene contexts
We propose a robust scene recognition framework using scene context information for multimedia contents. Multimedia contents consist of scene sequences that are more likely to hap...
Ryoichi Ando, Koichi Shinoda, Sadaoki Furui, Takah...
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
15 years 8 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong