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CLOTH BAG OBJECT DETECTION USING THE YOLO ALGORITHM (YOU ONLY SEE ONCE) V5

Authors :
Rizki Hesananda
Desima Natasya
Ninuk Wiliani
Source :
Pilar Nusa Mandiri, Vol 18, Iss 2, Pp 217-222 (2023)
Publication Year :
2023
Publisher :
LPPM Nusa Mandiri, 2023.

Abstract

The use of plastic in modern life is increasing rapidly, causing the number of people who use plastic to increase, one of which is when shopping. The function of plastic bags as packaging for luggage is not comparable to the impact caused by plastic waste in the years to come. Plastic bags take a long time, even hundreds to thousands of years, to completely decompose. In order to support the government's program to reduce the use of plastic bags, this study will discuss how to detect cloth bags as a substitute for plastic bags. In this research, a system will be implemented to detect the use of cloth bags with Roboflow and Yolo v5. After carrying out all stages of the research, it can be concluded that the goodie bag detection model has been successfully created. The detection model was created using the YOLOV5 algorithm. The dataset used consists of 102 goodie bag images. The process model uses 100 epochs with the training result mAP@0.5 is 89.8%. So, in other words, it can be said that YOLO v5 can detect goodie bags very well.

Details

Language :
English, Indonesian
ISSN :
19781946 and 25276514
Volume :
18
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Pilar Nusa Mandiri
Publication Type :
Academic Journal
Accession number :
edsdoj.83dbde5d84914d15832f5cfdcd65ca8c
Document Type :
article
Full Text :
https://doi.org/10.33480/pilar.v18i2.3019