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Pengecaman insan berasaskan kaedah profil sentroid dan pengelas rangkaian neural buatan
Nooritawati Md Tahir1, Aini Hussain2, Salina Abdul Samad3, Hafizah Husain4.
In this study, centroidal profile which is a model based approach is employed for human recognition task. This is done by extracting unique representation of gait features of the subject automatically and passively from static images of human or non human. To evaluate the effectiveness of the generated centroidal profile, Artificial Neural Network (RNB) is used as classifier. Results attained proven that the centroidal profile is appropriate as feature extraction to be used as feature vectors for human shape classification based on classification rate of RNB achieved specifically above 98%.
Affiliation:
- Universiti Teknologi MARA, Malaysia
- Universiti Kebangsaan Malaysia, Malaysia
- Universiti Kebangsaan Malaysia, Malaysia
- Universiti Kebangsaan Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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