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An Object Detection and Scaling Model for Plastic Waste Sorting

Padalkar, Abhishek Sunil, Pathak, Pramod and Stynes, Paul (2021) An Object Detection and Scaling Model for Plastic Waste Sorting. In: Proceedings of the 1st International Conference on AI for People: Towards Sustainable AI, CAIP 2021, 20-24 November 2021, Bologna, Italy. CORE . EAI, Bologna, Italy, pp. 18-25. ISBN 978-1-63190-326-7

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Official URL: http://dx.doi.org/10.4108/eai.20-11-2021.2314204

Abstract

Plastic waste sorting involves the separation of plastic into its individual plastic types. This research proposes an Object Detection and Scaling Model for plastic waste sorting to detect four types of plastics using the WaDaBa dataset. This research compares the Object Detection and Scaling Models Scaled-Yolov4 and EfficientDet. Results demonstrate that Scaled-Yolov4-CSP outperforms the state of the art, Colour-Histogram based Canny-Edge-Gaussian Filter, by 21% accuracy.

Item Type: Book Section
Uncontrolled Keywords: Plastic Waste Sorting; Object Detection and Scaling Model; Scaled-Yolov4; EfficientDet
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software

G Geography. Anthropology. Recreation > GE Environmental Sciences > Environment
Divisions: School of Computing > Staff Research and Publications
Related URLs:
Depositing User: Clara Chan
Date Deposited: 04 Jan 2022 15:27
Last Modified: 15 Mar 2022 12:02
URI: http://norma.ncirl.ie/id/eprint/5257

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