Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network
Facial recognition is a part of Computer Vision that is used to get facial coordinates from an image. Many algorithms have been developed to support Facial Detection such as Cascade Face Detection using Haar-Like features and AdaBoost to classify its Cascade and Convolutional Neural Network (CNN). F...
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| Format: | Article |
| Language: | English |
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Ikatan Ahli Informatika Indonesia
2023-02-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Subjects: | |
| Online Access: | http://jurnal.iaii.or.id/index.php/RESTI/article/view/4437 |
| _version_ | 1797327694684225536 |
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| author | Umar Aditiawarman Dimas Erlangga Teddy Mantoro Lutfil Khakim |
| author_facet | Umar Aditiawarman Dimas Erlangga Teddy Mantoro Lutfil Khakim |
| author_sort | Umar Aditiawarman |
| collection | DOAJ |
| description | Facial recognition is a part of Computer Vision that is used to get facial coordinates from an image. Many algorithms have been developed to support Facial Detection such as Cascade Face Detection using Haar-Like features and AdaBoost to classify its Cascade and Convolutional Neural Network (CNN). Face recognition in this study uses the Deep Convolutional Neural Network (DCNN) method, and the output of this method is the measurement value of the face. In the model training process, Triplet Loss from Triplet Network Deep Metric Learning is used to get good face grouping results. The value of this face measurement will then be measured using the Euclidean distance calculation to determine the similarity of the input face from the dataset. This Research is using 6 images of Government officers in Indonesia to determine the accuracy of the model when there is a new picture of these officers inputted into the training machine. The result provides a 94% accuracy level with a variety of face positions and levels of brightness. |
| first_indexed | 2024-03-08T06:42:10Z |
| format | Article |
| id | doaj.art-5fb9adde71de49779bee0e69d056d4b8 |
| institution | Directory Open Access Journal |
| issn | 2580-0760 |
| language | English |
| last_indexed | 2024-03-08T06:42:10Z |
| publishDate | 2023-02-01 |
| publisher | Ikatan Ahli Informatika Indonesia |
| record_format | Article |
| series | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| spelling | doaj.art-5fb9adde71de49779bee0e69d056d4b82024-02-03T08:31:43ZengIkatan Ahli Informatika IndonesiaJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)2580-07602023-02-017111311910.29207/resti.v7i1.44374437Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural NetworkUmar Aditiawarman0Dimas Erlangga1Teddy Mantoro2Lutfil Khakim3Universitas Nusa PutraUniversitas Nusa PutraUniversitas SampoernaUniversitas Nusa PutraFacial recognition is a part of Computer Vision that is used to get facial coordinates from an image. Many algorithms have been developed to support Facial Detection such as Cascade Face Detection using Haar-Like features and AdaBoost to classify its Cascade and Convolutional Neural Network (CNN). Face recognition in this study uses the Deep Convolutional Neural Network (DCNN) method, and the output of this method is the measurement value of the face. In the model training process, Triplet Loss from Triplet Network Deep Metric Learning is used to get good face grouping results. The value of this face measurement will then be measured using the Euclidean distance calculation to determine the similarity of the input face from the dataset. This Research is using 6 images of Government officers in Indonesia to determine the accuracy of the model when there is a new picture of these officers inputted into the training machine. The result provides a 94% accuracy level with a variety of face positions and levels of brightness.http://jurnal.iaii.or.id/index.php/RESTI/article/view/4437face recognitiondeep convolutional neural networkfacenethaar cascaded classifier |
| spellingShingle | Umar Aditiawarman Dimas Erlangga Teddy Mantoro Lutfil Khakim Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) face recognition deep convolutional neural network facenet haar cascaded classifier |
| title | Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network |
| title_full | Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network |
| title_fullStr | Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network |
| title_full_unstemmed | Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network |
| title_short | Face Recognition of Indonesia’s Top Government Officials Using Deep Convolutional Neural Network |
| title_sort | face recognition of indonesia s top government officials using deep convolutional neural network |
| topic | face recognition deep convolutional neural network facenet haar cascaded classifier |
| url | http://jurnal.iaii.or.id/index.php/RESTI/article/view/4437 |
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