Waste plastic bottles classification with deep learning model
by Jixu Hou; Xiaofeng Xie; Wenwen Wang; Qian Cai; Zhengjie Deng; Houqun Yang; Hongnian Huang; Yizhen Wang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 25, No. 3, 2023

Abstract: The misuse of plastic products has led to serious environment problem. To alleviate such phenomenon, we need to recover the plastic waste with a precise distinction. In this work, we applied a deep learning model, e.g., Faster-RCNN, to identify the class of plastic bottle. We have designed a waste plastic bottle recycling system, which can cooperate with the manipulator and conveyor to automatically sort the bottles in the garbage. During the experiment, we established a data set containing 8400 images. Different backbone networks are used to train on the data set. The experimental results show that the skeleton network using Resnet-50 as Faster-RCNN has higher detection performance than other networks. The system can also be applied to the identification and classification of other solid wastes.

Online publication date: Fri, 03-Nov-2023

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