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HIS
2004
15 years 7 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
ICDE
2000
IEEE
189views Database» more  ICDE 2000»
16 years 7 months ago
Image Database Retrieval with Multiple-Instance Learning Techniques
In this paper, we develop and test an approach to retrieving images from an image database based on content similarity. First, each picture is divided into many overlapping region...
Cheng Yang, Tomás Lozano-Pérez
DATE
2009
IEEE
107views Hardware» more  DATE 2009»
16 years 1 months ago
Learning early-stage platform dimensioning from late-stage timing verification
— Today's innovations in the automotive sector are, to a great extent, based on electronics. The increasing integration complexity and stringent cost reduction goals turn E/...
Kai Richter, Marek Jersak, Rolf Ernst
ICASSP
2008
IEEE
16 years 24 days ago
Multiple kernel learning for speaker verification
Many speaker verification (SV) systems combine multiple classifiers using score-fusion to improve system performance. For SVM classifiers, an alternative strategy is to combine...
Chris Longworth, Mark J. F. Gales
ICB
2007
Springer
308views Biometrics» more  ICB 2007»
16 years 15 days ago
Learning Multi-scale Block Local Binary Patterns for Face Recognition
Abstract. In this paper, we propose a novel representation, called Multiscale Block Local Binary Pattern (MB-LBP), and apply it to face recognition. The Local Binary Pattern (LBP) ...
ShengCai Liao, XiangXin Zhu, Zhen Lei, Lun Zhang, ...