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INTERSPEECH
2010
14 years 8 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
ICASSP
2011
IEEE
14 years 5 months ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li
ECCV
1998
Springer
16 years 3 months ago
Is Machine Colour Constancy Good Enough?
This paper presents a negative result: current machine colour constancy algorithms are not good enough for colour-based object recognition. This result has surprised us since we ha...
Brian V. Funt, Kobus Barnard, Lindsay Martin
103
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ICB
2007
Springer
144views Biometrics» more  ICB 2007»
15 years 5 months ago
Face Recognition with Local Gabor Textons
This paper proposes a novel face representation and recognition method based on local Gabor textons. Textons, defined as a vocabulary of local characteristic features, are a good d...
Zhen Lei, Stan Z. Li, Rufeng Chu, XiangXin Zhu
PAKDD
2009
ACM
103views Data Mining» more  PAKDD 2009»
15 years 8 months ago
Hot Item Detection in Uncertain Data
Abstract. An object o of a database D is called a hot item, if there is a sufficiently large population of other objects in D that are similar to o. In other words, hot items are ...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...