KURNIAWAN, DICKY GIANCINI ARWINDO (2021) IDENTIFIKASI PENGGUNAAN MASKER MENGGUNAKAN ARSITEKTUR YOLOV3 (YOU ONLY LOOK ONCE). Undergraduate thesis, UPN"VETERAN" JATIM.
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Abstract
With the COVID-19 pandemic, health protocols such as: maintain social distance, wash hands with soap regularly, and use masks are a directive given by the World Health Organization (WHO) to reduce the risk of spreading the COVID-19 virus. But with According to the directive, there are still people who are not wearing masks in the place general. The emergence of trending Machine Learning and Deep Learning creates various researches to find new methods and cutting-edge architecture such as YOLOv3 (You Only Look Once). YOLOv3 is a detector architecture which is claimed to be the “fastest deep learning object detector” which sacrifices accuracy with speed. Using YOLOv3, we can create robust and precise mask detection to detect whether someone visible in the image can be recognized using a mask or not. With base deep YOLOv3 architecture, then some aspects of research trials will be carried out such as trials with small, large amounts of data, augmentation and do not use augmentation. By doing the augmentation process and the amount a lot of data, then the results obtained are a large accuracy evaluation, namely: 0.99 mAP for the amount of data 800 and with the augmentation process. Keywords: Image, Deep Learning, Masks, Mask Identification, YOLOv3
| Item Type: | Thesis (Undergraduate) | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||
| Depositing User: | Mujari Mujari | ||||||||
| Date Deposited: | 22 Jun 2021 02:59 | ||||||||
| Last Modified: | 22 Jun 2021 03:00 | ||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/2083 |
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