Real-time Sorting of Plastic Waste for Pre-Cleaning Recycle

Conference proceedings article

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Publication Details

Author list: Jaruprathai K.; Youngkong P.

Publisher: Institute of Electrical and Electronics Engineers Inc.

Publication year: 2025

ISBN: 979-833154395-2

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007142319&doi=10.1109%2fiEECON64081.2025.10987820&partnerID=40&md5=9f57f0d6f3cde6f8eb2427dbc19501ab

Languages: English-Great Britain (EN-GB)

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Abstract

Despite Thailand's longstanding efforts in plastic waste sorting, a substantial portion remains unrecycled. This paper introduces an innovative approach utilizing the YOLOv8s deep learning algorithm for real-time plastic waste sorting, specifically targeting five categories: bottles (left and right), glass (left and right), and food containers. The dataset comprises 408 images of everyday plastic waste, including grayscale variations. Our experimental results demonstrate an average F1-score of 85%, precision of 96.6%, precision-recall of 89%, and a confusion matrix showing classification confidence levels of 100% for bottle left and food containers, 87% for bottle right and 86% for glass right. © 2025 IEEE.

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