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Title	Automatic Classifications And Recognition For Recycled Garbage By Utilizing Deep Learning Technology
ID_Doc	11292
Authors	HuiYu L.; Owolabi Ganiyat O.; Kim S.-H.
Year	2019
Published	ACM International Conference Proceeding Series
DOI	http://dx.doi.org/10.1145/3377170.3377190
Abstract	The increasingly serious environmental problems have posed new challenges to the survival of human beings, an average of 1269 tons of garbage is produced every day in Kwangju, South Korea. Most of them can be recycled, however, it costs a lot of manpower and resources and satisfactory classification efficiency was not achieved. Therefore, how to classify recycled garbage efficiently and accurately has become an important research direction. This paper proposes a novel classification method to automatically identify the type of garbage by utilizing deep learning technology. Deep learning technology is wildly utilized for image classification. Therefore, it also applies to the classification of recycled garbage. It not only saves a lot of manpower and resources but also improves the utilization of recycled resources. © 2019 Association for Computing Machinery.
Author Keywords	Computer vision; Convolutional neural networks; Deep learning; Image processing; Waste classification

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