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» Textural Features for Hyperspectral Pixel Classification
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PRL
2008
152views more  PRL 2008»
13 years 7 months ago
WND-CHARM: Multi-purpose image classification using compound image transforms
We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classificati...
Nikita Orlov, Lior Shamir, Tomasz J. Macura, Josia...
TIP
2002
179views more  TIP 2002»
13 years 7 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
MVA
2007
211views Computer Vision» more  MVA 2007»
13 years 9 months ago
Shadow Elimination in Traffic Video Segmentation
Shadow detection is critical for robust and reliable vision-based systems for traffic vision analysis. Shadow points are often misclassified as object points causing errors in loc...
Hong Liu, Jintao Li, Qun Liu, Yueliang Qian
CVPR
2007
IEEE
14 years 9 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs
BMVC
2010
13 years 5 months ago
Classifying Textile Designs using Region Graphs
Markov random field pixel labelling is often used to obtain image segmentations in which each segment or region is labelled according to its attributes such as colour or texture. ...
Wei Jia, Stephen J. McKenna, Annette A. Ward, Keit...