scholarly journals An adaptive approach for Human Emotions Recognition System for Neural Networks using Hidden Markov Model and Self Organizing Maps algorithms

2021 ◽  
Author(s):  
K.M. Azaraffali ◽  
Dr.T. Krishnakumar ◽  
Dr.M. Sriram
Keyword(s):  
Neural Networks ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Recognition System ◽  
Self Organizing Maps ◽  
Adaptive Approach ◽  
Human Emotions ◽  
Self Organizing

Auscultating Diagnosis for Hemodialysis Shunt Stenosis using a Self-Organizing Map and Hidden Markov Model

2012 ◽  
Vol 132 (10) ◽  
pp. 1589-1594 ◽  
Author(s):  
Hayato Waki ◽  
Yutaka Suzuki ◽  
Osamu Sakata ◽  
Mizuya Fukasawa ◽  
Hatsuhiro Kato
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Self Organizing Map ◽  
Self Organizing

Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

2014 ◽  
Author(s):  
Jing Jin ◽  
Yuanqing Wang ◽  
Liujing Xu ◽  
Liqun Cao ◽  
Lei Han ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Face Detection ◽  
Gesture Recognition ◽  
Hidden Markov ◽  
Recognition System

Hidden Markov model interpretations of neural networks

2000 ◽  
Vol 23 (4) ◽  
pp. 494-495
Author(s):  
Ingmar Visser
Keyword(s):  
Neural Networks ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Distributed Representations ◽  
Hidden Layer

Page's manifesto makes a case for localist representations in neural networks, one of the advantages being ease of interpretation. However, even localist networks can be hard to interpret, especially when at some hidden layer of the network distributed representations are employed, as is often the case. Hidden Markov models can be used to provide useful interpretable representations.

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