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» Experiments with a New Boosting Algorithm
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ICML
2005
IEEE
15 years 10 months ago
Ensembles of biased classifiers
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
Andreas Heß, Nicholas Kushmerick, Rinat Khou...
AVBPA
2003
Springer
133views Biometrics» more  AVBPA 2003»
15 years 1 months ago
LUT-Based Adaboost for Gender Classification
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
Bo Wu, Haizhou Ai, Chang Huang
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
ICC
2007
IEEE
15 years 1 months ago
A New Relaxation Labeling Architecture for Secure Localization in Sensor Networks
In this paper, a new strategy is proposed to defend against colluding malicious nodes in a sensor network. The new strategy is based on a new relaxation labeling algorithm to class...
Chih-Chieh Geoff Chang, Wesley E. Snyder, Cliff Wa...
TSMC
2008
198views more  TSMC 2008»
14 years 9 months ago
Representation Plurality and Fusion for 3-D Face Recognition
In this paper, we present an extensive study of 3-D face recognition algorithms and examine the benefits of various score-, rank-, and decision-level fusion rules. We investigate f...
Berk Gökberk, Helin Dutagaci, A. Ulas, Lale A...