| dc.contributor.author | Muhammad Naufal, Mansor | |
| dc.contributor.author | Sazali, Yaacob, Prof. Dr. | |
| dc.contributor.author | Hariharan, Muthusamy, Dr. | |
| dc.contributor.author | Shafriza Nisha, Basah, Dr. | |
| dc.contributor.author | Mohd Nazri, Rejab | |
| dc.date.accessioned | 2014-05-02T08:23:27Z | |
| dc.date.available | 2014-05-02T08:23:27Z | |
| dc.date.issued | 2013-11 | |
| dc.identifier.citation | Advanced Science Letters, vol. 19(11), 2013, pages 3289-3292 | en_US |
| dc.identifier.issn | 1936-6612 | |
| dc.identifier.uri | http://www.ingentaconnect.com/content/asp/asl/2013/00000019/00000011/art00037?token=004612e07a5a666f3a7b6c2a4042423b475f6648783449264f655d375c6b6876305021 | |
| dc.identifier.uri | http://dspace.unimap.edu.my:80/dspace/handle/123456789/34215 | |
| dc.description | Link to publisher's homepage at www.aspbs.com/ | en_US |
| dc.description.abstract | 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 k-Nearest Neighbour (k-NN) with 96.78% accuracy was accepted. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | American Scientific Publishers All rights reserved. | en_US |
| dc.subject | AR model | en_US |
| dc.subject | Infant hungry recognition | en_US |
| dc.subject | K-NN | en_US |
| dc.title | Infant hungry recognition based on k-NN and Autoregressive Model | en_US |
| dc.type | Article | en_US |
| dc.contributor.url | apairia@yahoo.com | en_US |
| dc.contributor.url | s.yaacob@unimap.edu.my | en_US |
| dc.contributor.url | hari@unimap.edu.my | en_US |
| dc.contributor.url | shafriza@unimap.edu.my | en_US |
