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» SVM optimization: inverse dependence on training set size
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ICIP
2000
IEEE
14 years 9 months ago
Look up Table (LUT) Method for Image Halftoning
Recently we have applied Look Up Table (LUT) Method for inverse halftoning. We also proposed tree-structure LUT inverse halftoning in order to reduce memory requirements of the LU...
Murat Mese, Palghat P. Vaidyanathan
AIME
2009
Springer
13 years 5 months ago
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Aliaksei Kerhet, Cormac Small, Harvey Quon, Terenc...
CVPR
2011
IEEE
13 years 4 months ago
Saliency Estimation Using a Non-Parametric Low-Level Vision Model
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
13 years 11 months ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
11 years 9 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman