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» Lightweight Extraction of Object Models from Bytecode
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CVPR
2011
IEEE
13 years 4 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ICML
2007
IEEE
14 years 8 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
ICMCS
2007
IEEE
155views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Hidden Maximum Entropy Approach for Visual Concept Modeling
Recently, the bag-of-words approach has been successfully applied to automatic image annotation, object recognition, etc. The method needs to first quantize an image using the vis...
Sheng Gao, Joo-Hwee Lim, Qibin Sun
ICIP
2008
IEEE
14 years 2 months ago
Dynamic background modeling and subtraction using spatio-temporal local binary patterns
Traditional background modeling and subtraction methods have a strong assumption that the scenes are of static structures with limited perturbation. These methods will perform poo...
Shengping Zhang, Hongxun Yao, Shaohui Liu
PKDD
2000
Springer
151views Data Mining» more  PKDD 2000»
13 years 11 months ago
Discovery of Characteristic subgraph Patterns Using Relative Indexing and the Cascade Model
: Relational representation of objects using graphs reveals much information that cannot be obtained by attribute value representations alone. There are already many databases that...
Takashi Okada, Mayumi Oyama