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» Learning of Boolean Functions Using Support Vector Machines
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BMCBI
2007
207views more  BMCBI 2007»
13 years 9 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
ISNN
2005
Springer
14 years 2 months ago
Content Based Retrieval and Classification of Cultural Relic Images
In this paper we present a novel system for content-based retrieval and classification of cultural relic images. First, the images are normalized to achieve rotation, translation a...
Na Wei, M. Emre Celebi, Guohua Geng
CVPR
2001
IEEE
14 years 11 months ago
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
CVPR
2001
IEEE
14 years 11 months ago
Component-based Face Detection
We present a component-based, trainable system for detecting frontal and near-frontal views of faces in still gray images. The system consists of a two-level hierarchy of Support ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
ICIP
2005
IEEE
14 years 11 months ago
Lung nodules detection and classification
Image processing techniques and Computer Aided Diagnosis (CAD) systems have proved to be effective for the improvement of radiologists' diagnosis. In this paper an automatic ...
Paola Campadelli, Elena Casiraghi, Giorgio Valenti...