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ECCV
2010
Springer
13 years 5 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
WWW
2010
ACM
13 years 11 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft
SMC
2007
IEEE
156views Control Systems» more  SMC 2007»
13 years 11 months ago
Dynamic fusion of classifiers for fault diagnosis
—This paper considers the problem of temporally fusing classifier outputs to improve the overall diagnostic classification accuracy in safety-critical systems. Here, we discuss d...
Satnam Singh, Kihoon Choi, Anuradha Kodali, Krishn...
BMCBI
2004
208views more  BMCBI 2004»
13 years 4 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
BMCBI
2010
111views more  BMCBI 2010»
13 years 4 months ago
Functional Analysis: Evaluation of Response Intensities - Tailoring ANOVA for Lists of Expression Subsets
Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions....
Fabrice Berger, Bertrand De Meulder, Anthoula Gaig...