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FLAIRS
2004
13 years 10 months ago
Case-Based Bayesian Network Classifiers
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Eugene Santos, Ahmed Huessin
ACCV
2007
Springer
14 years 21 days ago
A Cascade of Feed-Forward Classifiers for Fast Pedestrian Detection
We develop a method that can detect humans in a single image based on a new cascaded structure. In our approach, both the rectangle features and 1-D edge-orientation features are e...
Yu-Ting Chen, Chu-Song Chen
SGAI
2004
Springer
14 years 2 months ago
Interactive Selection of Visual Features through Reinforcement Learning
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Sébastien Jodogne, Justus H. Piater
BMCBI
2010
164views more  BMCBI 2010»
13 years 6 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
BMCBI
2006
158views more  BMCBI 2006»
13 years 8 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...