Sistem Pendeteksi Sampah Secara Realtime Menggunakan Metode YOLO

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 garbage.

Keywords: YOLO, Convolutional Neural Network, Sampah, object detection