DocumentCode
1632572
Title
Infant hungry recognition based on neural network and AR model
Author
Mansor, M.N. ; Rejab, M.N. ; Syam, S.H.-F. ; Syam, A.H.-F.
Author_Institution
Sch. of Mechatron. Eng., Univ. Malaysia Perlis, Kangar, Malaysia
Volume
2
fYear
2012
Firstpage
368
Lastpage
370
Abstract
To deal with nonverbal life was a difficult task. To study their behaviour without knowing what their needs is another crucial issue. A lot of researches have been rapidly investigated. Thus, in this paper we proudly proposed a system to determine the hungry infant based on their facial expression. A Haar Cascade face detection method was implemented. Autoregressive Model (AR) was employed for the coefficient extraction. Some other statistical methods were used as the feature extraction. Finally Neural network (NN) with 93.78% accuracy was accepted.
Keywords
emotion recognition; face recognition; AR model; Haar Cascade face detection method; autoregressive model; facial expression; infant hungry recognition; neural network; nonverbal life; Educational institutions; Feature extraction; Mathematical model; Neural networks; Pediatrics; Training; Video recording; Autoregressive Model (AR); Detection of facial changes; NICU patient; Neural Network classifier;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location
Sanya
Print_ISBN
978-1-4673-2465-6
Type
conf
DOI
10.1109/MSNA.2012.6324596
Filename
6324596
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