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» Combining Methods for Dynamic Multiple Classifier Systems
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91
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ICIP
2007
IEEE
15 years 4 months ago
Computer-Aided Grading of Neuroblastic Differentiation: Multi-Resolution and Multi-Classifier Approach
In this paper, the development of a computer-aided system for the classification of grade of neuroblastic differentiation is presented. This automated process is carried out withi...
Jun Kong, Olcay Sertel, Hiroyuki Shimada, Kim L. B...
89
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Geometric programming for aggregation of binary classifiers
Multiclass classification problems are often decomposed into multiple binary problems that are solved by individual binary classifiers whose results are integrated into a final...
Sunho Park, Seungjin Choi
79
Voted
ICPR
2006
IEEE
16 years 1 months ago
Modification of the AdaBoost-based Detector for Partially Occluded Faces
While face detection seems a solved problem under general conditions, most state-of-the-art systems degrade rapidly when faces are partially occluded by other objects. This paper ...
Jie Chen, Shiguang Shan, Shengye Yan, Xilin Chen, ...
88
Voted
ECML
2005
Springer
15 years 6 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu
115
Voted
BMCBI
2010
152views more  BMCBI 2010»
15 years 17 days ago
Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks
Background: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed...
Martin T. Swain, Johannes J. Mandel, Werner Dubitz...