Prasetyo, Mochammad Langgeng and Wibowo, Achmad Teguh and Ridwan, Mujib and Milad, Mohammad Khusnul and Arifin, Sirajul and Izzuddin, Muhammad Andik and Setyowati, Rr Diah Nugraheni and Ernawan, Ferda (2021) Face recognition using the convolutional neural network for Barrier Gate System. iJIM: International Journal of Interactive Mobile Technologies, 15 (10). pp. 138-153. ISSN 1865-7923
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Abstract
The implementation of face recognition technique using CCTV is able to prevent unauthorized person enter the gate. Face recognition can be used for authentication, which can be implemented for preventing of criminal incidents. This re-search proposed a face recognition system using convolutional neural network to open and close the real-time barrier gate. The process consists of a convolutional layer, pooling layer, max pooling, flattening, and fully connected layer for detecting a face. The information was sent to the microcontroller using Internet of Thing (IoT) for ontrolling the barrier gate. The face recognition results are used to open or close the gate in the real time. The experimental results obtained average error rate of 0.320 and the accuracy of success rate is about 93.3%. The average response time required by microcontroller is about 0.562ms. The simulation result show that the face recognition technique using CNN is highly recommended to be implemented in barrier gate system.
Item Type: | Article |
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Additional Information: | https://online-journals.org/index.php/i-jim/article/view/20175 |
Creators: | Creators Email ["eprint_fieldname_creators_NIDN" not defined] Prasetyo, Mochammad Langgeng - - Wibowo, Achmad Teguh atw@uinsby.ac.id 2026108801 Ridwan, Mujib mujibrw@uinsby.ac.id 2027048602 Milad, Mohammad Khusnul m.milad@uinsby.ac.id 0729017902 Arifin, Sirajul sirajul.arifin@yahoo.com; sirajul.arifin@uinsby.ac.id 2014057001 Izzuddin, Muhammad Andik andik32@gmail.com 2007038402 Setyowati, Rr Diah Nugraheni diahnugraheni@uinsby.ac.id 198205012014032001 Ernawan, Ferda - - |
Uncontrolled Keywords: | Barrier gate system; convolutional neural network; face recognition; IoT |
Subjects: | 08 INFORMATION AND COMPUTING SCIENCES > 0805 Distributed Computing > 080503 Networking and Communications |
Divisions: | Karya Ilmiah > Artikel |
Depositing User: | Susilo Joko |
Date Deposited: | 24 Aug 2021 03:36 |
Last Modified: | 17 Sep 2021 03:44 |
URI: | http://repository.uinsa.ac.id/id/eprint/40 |