Sistem Pendeteksi Sampah Secara Realtime Menggunakan Metode YOLO

Authors

  • Kadek Adi Priana Universitas Udayana Author
  • Anak Agung Istri Ngurah Eka Karyawati Universitas Udayana Author

DOI:

https://doi.org/10.24843/JNATIA.2023.v02.i01.p04

Keywords:

YOLO, Convolutional Neural Network, Sampah, object detection

Abstract

At present, people’s daily garbage is increasing day by day. How to intelligently classify garbage can save manpower and improve work efficiency. In this paper, a garbage classification model is based on. First, according to the common daily garbage category, twelve typical kinds of garbage were selected, data cleaned, labeled, and constructed a garbage dataset. Second, YOLO was built and trained on our datasets. The experimental results show that YOLO can accurately identify the garbage’s types and find out the location of garbag 

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Published

2023-11-01

How to Cite

[1]
Kadek Adi Priana and Anak Agung Istri Ngurah Eka Karyawati, “Sistem Pendeteksi Sampah Secara Realtime Menggunakan Metode YOLO”, Jnatia, vol. 2, no. 1, pp. 31–36, Nov. 2023, doi: 10.24843/JNATIA.2023.v02.i01.p04.

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