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» Learning Mid-Level Features For Recognition
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ICIP
2010
IEEE
13 years 5 months ago
Texture classification via patch-based sparse texton learning
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling textur...
Jin Xie, Lei Zhang, Jane You, David Zhang
JMLR
2010
185views more  JMLR 2010»
13 years 2 months ago
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
Franz Pernkopf, Jeff A. Bilmes
CVPR
2012
IEEE
11 years 10 months ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
ICIP
2007
IEEE
14 years 1 months ago
Group Activity Recognition Based on ARMA Shape Sequence Modeling
In this paper, we propose a system identification approach for group activity recognition in traffic surveillance. Statistical shape theory is used to extract features, and then...
Ying Wang, Kaiqi Huang, Tieniu Tan
IJDAR
2006
131views more  IJDAR 2006»
13 years 7 months ago
Genetic engineering of hierarchical fuzzy regional representations for handwritten character recognition
This paper presents a genetic programming based approach for optimizing the feature extraction step of a handwritten character recognizer. This recognizer uses a simple multilayer ...
Christian Gagné, Marc Parizeau