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- W4312081662 abstract "The rapid social development has given rise to a growing concern over environmental issues, one of which is the disposal of solid waste. Recycling is considered as one of the critical disposal methods. Taking into consideration of fast, intelligent classification and identification of the solid waste as a prerequisite for recycling and utilization, a multiple material feature based solid waste identification and classification method is proposed in this paper. The experimental results show that the proposed method achieves an accuracy of 83.7 <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>%</sup> on an in-house textile solid waste image dataset. The results indicates that our method with multiple material features is able to handle the textile solid waste recognition problem properly." @default.
- W4312081662 created "2023-01-04" @default.
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- W4312081662 date "2022-11-01" @default.
- W4312081662 modified "2023-09-28" @default.
- W4312081662 title "Textile Solid Waste Recognition with Multiple Material Features" @default.
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- W4312081662 doi "https://doi.org/10.1109/ccisp55629.2022.9974371" @default.
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