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TMM
2002
104views more  TMM 2002»
13 years 7 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
TIP
2002
133views more  TIP 2002»
13 years 7 months ago
Wavelet-based rotational invariant roughness features for texture classification and segmentation
In this paper, we introduce a rotational invariant feature set for texture segmentation and classification, based on an extension of fractal dimension (FD) features. The FD extract...
Dimitrios Charalampidis, Takis Kasparis
ICIP
2009
IEEE
14 years 8 months ago
Optimum Kernel Function Design From Scale Space Features For Object Detection
Scale-space representation of an image is a significant way to generate features for classification. However, for a specific classification task, the entire scale-space may not be...
ICIP
2003
IEEE
14 years 9 months ago
Histogram intersection kernel for image classification
In this paper we address the problem of classifying images, by exploiting global features that describe color and illumination properties, and by using the statistical learning pa...
Annalisa Barla, Francesca Odone, Alessandro Verri
PCM
2007
Springer
132views Multimedia» more  PCM 2007»
14 years 1 months ago
FADA: An Efficient Dimension Reduction Scheme for Image Classification
This paper develops a novel and efficient dimension reduction scheme--Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sampl...
Yijuan Lu, Jingsheng Ma, Qi Tian