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» Fuzzy Observable Markov Models for Pattern Recognition
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ICPR
2000
IEEE
15 years 1 months ago
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...
ATAL
2006
Springer
15 years 1 months ago
Robust recognition of physical team behaviors using spatio-temporal models
This paper presents a framework for robustly recognizing physical team behaviors by exploiting spatio-temporal patterns. Agent team behaviors in athletic and military domains typi...
Gita Sukthankar, Katia P. Sycara
DATE
2008
IEEE
136views Hardware» more  DATE 2008»
15 years 3 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
ISMB
1996
14 years 10 months ago
Gene Recognition in Cyanobacterium Genomic Sequence Data Using the Hidden Markov Model
We have developed a hidden Markov model (HMM)to detect the protein coding regions within one megabase contiguous sequence data, registered in a database called GenBankin eight ent...
Tetsushi Yada, Makoto Hirosawa
FLAIRS
2008
14 years 11 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar