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» Texture Feature Extraction and Classification
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120
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MVA
2006
120views Computer Vision» more  MVA 2006»
15 years 2 months ago
A model of diatom shape and texture for analysis, synthesis and identification
We describe tools for automatic identification and classification of diatoms that compare photographs with other photographs and drawings, via a model. Identification of diatoms, i...
Yulia Hicks, A. David Marshall, Paul L. Rosin, Ral...
139
Voted
ICCV
2007
IEEE
16 years 4 months ago
DynamicBoost: Boosting Time Series Generated by Dynamical Systems
Boosting is a remarkably simple and flexible classification algorithm with widespread applications in computer vision. However, the application of boosting to nonEuclidean, infini...
René Vidal, Paolo Favaro
140
Voted
ICVGIP
2008
15 years 4 months ago
Object Category Recognition with Projected Texture
Recognition of object categories from their images is extremely challenging due to the large intra-class variations, and variations in pose, illumination and scale, in addition to...
Avinash Sharma, Anoop M. Namboodiri
IJCNN
2008
IEEE
15 years 9 months ago
Multifractal feature vectors for Brain-Computer interfaces
—This article introduces a new feature vector extraction for EEG signals using multifractal analysis. The validity of the approach is asserted on real data sets from the BCI comp...
Nicolas Brodu
98
Voted
CORR
2006
Springer
93views Education» more  CORR 2006»
15 years 2 months ago
Functional dissipation microarrays for classification
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...