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» Fuzzy Observable Markov Models for Pattern Recognition
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ICPR
2000
IEEE
15 years 11 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 10 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»
16 years 29 days 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
15 years 7 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
15 years 8 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