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» Combining Methods for Dynamic Multiple Classifier Systems
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IPMI
2003
Springer
16 years 1 months ago
Expectation Maximization Strategies for Multi-atlas Multi-label Segmentation
It is well-known in the pattern recognition community that the accuracy of classifications obtained by combining decisions made by independent classifiers can be substantially high...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
ICML
2006
IEEE
16 years 1 months ago
Combined central and subspace clustering for computer vision applications
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
Le Lu, René Vidal
110
Voted
ACL
2007
15 years 2 months ago
Improved Word-Level System Combination for Machine Translation
Recently, confusion network decoding has been applied in machine translation system combination. Due to errors in the hypothesis alignment, decoding may result in ungrammatical co...
Antti-Veikko I. Rosti, Spyridon Matsoukas, Richard...
118
Voted
TIFS
2010
137views more  TIFS 2010»
14 years 7 months ago
On the dynamic selection of biometric fusion algorithms
Biometric fusion consolidates the output of multiple biometric classifiers to render a decision about the identity of an individual. We consider the problem of designing a fusion s...
Mayank Vatsa, Richa Singh, Afzel Noore, Arun Ross
110
Voted
AIPR
2003
IEEE
15 years 4 months ago
Sensor and Classifier Fusion for Outdoor Obstacle Detection: an Application of Data Fusion To Autonomous Off-Road Navigation
This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation. We are focusing on outdoor obstacle detection, and we pre...
Cristian Dima, Nicolas Vandapel, Martial Hebert