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» Iterative Feature Selection for Color Texture Classification
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ICMCS
2006
IEEE
182views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Using Semantic Features for Scene Classification: how Good do they Need to Be?
Semantic scene classification is a useful, yet challenging problem in image understanding. Most existing systems are based on low-level features, such as color or texture, and suc...
Matthew R. Boutell, Anustup Choudhury, Jiebo Luo, ...
SETN
2004
Springer
14 years 27 days ago
An Intelligent System for Aerial Image Retrieval and Classification
Content based image retrieval is an active research area of pattern recognition. A new method of extracting global texture energy descriptors is proposed and it is combined with fe...
Antonios Gasteratos, Panagiotis Zafeiridis, Ioanni...
CVPR
2008
IEEE
14 years 9 months ago
Image decomposition into structure and texture subcomponents with multifrequency modulation constraints
Texture information in images is coupled with geometric macrostructures and piecewise-smooth intensity variations. Decomposing an image f into a geometric structure component u an...
Georgios Evangelopoulos, Petros Maragos
IDEAL
2005
Springer
14 years 1 months ago
Evolving Neural Networks for the Classification of Malignancy Associated Changes
Malignancy Associated Changes are subtle changes to the nuclear texture of visually normal cells in the vicinity of a cancerous or precancerous lesion. We describe a classifier for...
Jennifer Hallinan
ICCV
2003
IEEE
14 years 9 months ago
Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Xiang Sean Zhou, Dorin Comaniciu, Arun Krishnan