Pamungkas, Bima putra Gusti (2020) IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK UNTUK MENGHITUNG SEKUMPULAN MANUSIA. Undergraduate thesis, UPN"VETERAN" JATIM.
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Abstract
The use of elevators in high-rise buildings is very important for meet the need for time efficiency so as to improve performance human. The number of humans is increasing day by day when compared with a small lift capacity eventually creates a new problem, namely when the number of people is not proportional to the available space capacity. Calculate the number of people in the elevator can provide information for managers in optimizing the place and also evaluating the number of man in an operating elevator. This study uses video results cctv elevator recording that can facilitate the process of human identification from the inside elevator room. The algorithms used are YOLOv3 and YOLOv2 which is one of the algorithms of the Deep Learning network as a method deep learning to detect and count humans. Results that obtained by using the YOLOv3 model more with an average value of confidence 0.90 compared to YOLOv2 which has an average value of confidence 0.61. This is because YOLOv3 has more layers compared to YOLOv2. However, the time required in running programs with YOLOv3 takes longer than with YOLOv2. Keyword : Elevator, Human, YOLO-CNN
| Item Type: | Thesis (Undergraduate) | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76.76.E95 Expert Systems | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||
| Depositing User: | Mujari Mujari | ||||||||
| Date Deposited: | 22 Jun 2021 03:21 | ||||||||
| Last Modified: | 22 Jun 2021 03:22 | ||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/2064 |
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