Research Article
An Object Detection and Scaling Model for Plastic Waste Sorting
@INPROCEEDINGS{10.4108/eai.20-11-2021.2314204, author={Abhishek Padalkar and Pramod Pathak and Paul Stynes}, title={An Object Detection and Scaling Model for Plastic Waste Sorting}, proceedings={Proceedings of the 1st International Conference on AI for People: Towards Sustainable AI, CAIP 2021, 20-24 November 2021, Bologna, Italy}, publisher={EAI}, proceedings_a={CAIP}, year={2021}, month={12}, keywords={plastic waste sorting object detection and scaling model scaled-yolov4 efficientdet}, doi={10.4108/eai.20-11-2021.2314204} }- Abhishek Padalkar
Pramod Pathak
Paul Stynes
Year: 2021
An Object Detection and Scaling Model for Plastic Waste Sorting
CAIP
EAI
DOI: 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.
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