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MCS
2001
Springer
13 years 12 months ago
Error Rejection in Linearly Combined Multiple Classifiers
In this paper, the error-reject trade-off of linearly combined multiple classifiers is analysed in the framework of the minimum risk theory. Theoretical analysis described in [12,1...
Giorgio Fumera, Fabio Roli
ICPR
2004
IEEE
14 years 8 months ago
Probabilistic Combination of Multiple Modalities to Detect Interest
This paper describes a new approach to combine multiple modalities and applies it to the problem of affect recognition. The problem is posed as a combination of classifiers in a p...
Ashish Kapoor, Rosalind W. Picard, Yuri Ivanov
PRIS
2004
13 years 9 months ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred
CVPR
2008
IEEE
14 years 9 months ago
Towards unsupervised whole-object segmentation: Combining automated matting with boundary detection
We propose a novel step toward the unsupervised segmentation of whole objects by combining "hints" of partial scene segmentation offered by multiple soft, binary mattes....
Andrew N. Stein, Thomas S. Stepleton, Martial Hebe...
WIAMIS
2009
IEEE
14 years 2 months ago
Towards fully un-supervised methods for generating object detection classifiers using social data
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...
Spiros Nikolopoulos, Elisavet Chatzilari, Eirini G...