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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
15 years 4 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
ICCV
2011
IEEE
14 years 6 months ago
Scene Recognition and Weakly Supervised Object Localization with Deformable Part-Based Models
Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
Megha Pandey, Svetlana Lazebnik
ICCV
2011
IEEE
14 years 6 months ago
A String of Feature Graphs Model for Recognition of Complex Activities in Natural Videos
Videos usually consist of activities involving interactions between multiple actors, sometimes referred to as complex activities. Recognition of such activities requires modeling ...
Utkarsh Gaur, Yingying Zhu, Bi Song, Amit Roy-Chow...
ICASSP
2009
IEEE
16 years 1 months ago
Speech emotion recognition via a max-margin framework incorporating a loss function based on the Watson and Tellegen's emotion m
This paper considers a method for speech emotion recognition by a max-margin framework incorporating a loss function based on a well-known model called the Watson and Tellegen’s...
Sungrack Yun, Chang D. Yoo
ICDAR
2003
IEEE
16 years 4 days ago
Handwritten character recognition using elastic matching based on a class-dependent deformation model
For handwritten character recognition, a new elastic image matching (EM) technique based on a class-dependent deformation model is proposed. In the deformation model, any deformat...
Seiichi Uchida, Hiroaki Sakoe