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» Spectral Clustering and Embedding with Hidden Markov Models
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NIPS
2001
13 years 9 months ago
Dynamic Time-Alignment Kernel in Support Vector Machine
A new class of Support Vector Machine (SVM) that is applicable to sequential-pattern recognition such as speech recognition is developed by incorporating an idea of non-linear tim...
Hiroshi Shimodaira, K.-I. Noma, Mitsuru Nakai, Shi...
IEEEVAST
2010
13 years 2 months ago
A visual analytics approach to model learning
The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization sys...
Supriya Garg, I. V. Ramakrishnan, Klaus Mueller
CVPR
1997
IEEE
13 years 11 months ago
LAFTER: Lips and Face Real-Time Tracker
This paper describes an active-camera real-time system for tracking, shape description, and classification of the human face and mouth using only an SGI Indy computer. The system...
Nuria Oliver, Alex Pentland, François B&eac...
ANOR
2010
139views more  ANOR 2010»
13 years 5 months ago
Some operations research methods for analyzing protein sequences and structures
Operations Research is probably one of the most successful fields of applied mathematics used in Economics, Physics, Chemistry, almost everywhere onehastoanalyzehugeamountsofdata.L...
Piotr Lukasiak, Jacek Blazewicz, Maciej Milostan
TASLP
2010
157views more  TASLP 2010»
13 years 2 months ago
HMM-Based Reconstruction of Unreliable Spectrographic Data for Noise Robust Speech Recognition
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
Bengt J. Borgstrom, Abeer Alwan