Wulansari, Susanti Dewi (2020) Perancangan Sistem Kendali Akses Pintu Otomatis Berdasarkan Pengenalan Wajah Menggunakan Metode Deep Learning Fecenet dan MTCNN Berbasis Arduino Uno. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
The cases of theft and robbery are increasing from year to year, it makes people feel insecure and uncomfortable even at home. To increase the level of space security a program or security assistant is needed in real time to overcome the risk of a gap in a security itself. Along with current technological developments, one of them is to overcome this problem by using a biometric system that is used for facial image recognition. The human face consists of several parts that have their own characteristics, which extend from the forehead to the chin such as hair, forehead, eyes, nose, ears, cheeks, lips. This biometric technology is used as the basis for the detection system of the human body. In Deep Learning type neural networks each hidden layer is responsible for training a unique set of features based on the output from the previous network. This Algortima will become more complex and abstract when the number of hidden layers increases. One of the deep learning methods used for face recognition is Face-net. This method is for detecting faces specifically. Tests in this study used 270 face images for training data and 20 face images for test data. As well as 5 parameters of image conditions, namely normal, expressive, face direction, dim lighting, and distance to the webcam. The system accuracy in face recognition is 100%. Keywords: face recognition, automatic doors, image processing, deep learning, face-net.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Teknik Elektro |
| Depositing User: | Kaprodi Teknik Elektro |
| Date Deposited: | 20 Mar 2020 04:47 |
| Last Modified: | 20 Mar 2020 04:47 |
| URI: | http://eprints.uty.ac.id/id/eprint/4713 |
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