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- W4322731608 abstract "Urban regions produce a lot of solid trash, which needs to be processed individually for effective waste management since it contains a variety of diverse materials, including organic wastes, paper, plastic, metal, and glass. This suggests that the wastes that are deposited all at once need to be classified before being treated. Government created the idea of recyclable and organic wastes for citizens to dispose of trash in accordance with to encourage this process. The budget for waste segregation will be greatly reduced if these regulations are carefully adhered to, freeing up funds that may be used for more waste treatment. This study has used numpy, pandas, matplotlib, seaborn, python coco tools and pylab to categorize waste into each of its categories. This research study will make conclusions, determine the waste category and provide statistics for each.The code can be found at https://github.com/akshitachi/WasteDetection-And-Analysis." @default.
- W4322731608 created "2023-03-03" @default.
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- W4322731608 date "2023-01-05" @default.
- W4322731608 modified "2023-09-30" @default.
- W4322731608 title "Employing Machine Learning to Identify Waste Characteristics" @default.
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- W4322731608 doi "https://doi.org/10.1109/idciot56793.2023.10053527" @default.
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