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» Recognition of Parametrised Models from 3D Data
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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
16 years 1 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
ICASSP
2011
IEEE
14 years 5 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
ICB
2007
Springer
121views Biometrics» more  ICB 2007»
15 years 5 months ago
SVDD-Based Illumination Compensation for Face Recognition
Illumination change is one of most important and difficult problems which prevent from applying face recognition to real applications. For solving this, we propose a method to comp...
Sang-Woong Lee, Seong-Whan Lee
SSPR
2010
Springer
14 years 12 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
ICIP
2003
IEEE
16 years 3 months ago
Adaptive rule-based recognition of events in video sequences
Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is t...
Vassilis Tzouvaras, Gabriel Tsechpenakis, Giorgos ...