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Title |
Efficient and Smart Waste Categorization System using Deep Learning |
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Author |
Dr.P.Iyyanar, Dr.V Balaji, Dr.K. Ravikiran, K.V.Daya Sagar, Dr. Ravindra Raman Cholla, Dr. Kakoli Banerjee |
| Citation |
Vol. 22 No. 6 pp. 473-478 |
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Abstract |
The demand and importance of recycling are inevitable, considering either economic reasons or environmental reasons. This paper explains a smart waste categorization for a waste management system to efficiently segregate waste. This involves the deep learning model VGG16 which creates a waste management system that is capable to segregate the municipal waste into organic and inorganic waste and detecting the waste products that can be recycled. Doing these manually requires a lot of human power and managing the waste can be hazardous and can cause harm to both the health of the person collaborating with it and the environment. Using smart object identification software in waste sorting is a more strategic approach than traditional recycling methods because it identifies more objects in a shorter amount of time. The traditional approach relies on human goodwill and labour, both of which are vulnerable to failure in waste separation for recycling. As a result of this analysis, these can be avoided and advanced, as well as a fully automated waste management system constructed. |
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Keywords |
.Convolutional Neural Networks, Pre-train Model, Waste Separation, Automation, Support Vector Machine. |
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