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Smart city article details

Title	Garbage Classification And Analysis Using Deep Learning
ID_Doc	27708
Authors	Suman S.; Kurmi S.K.; Diwakar M.; Pandey N.K.; Singh P.; Madaan P.
Year	2025
Published	2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025
DOI	http://dx.doi.org/10.1109/IC363308.2025.10957447
Abstract	One of the biggest issues facing most municipalities worldwide is garbage management. Garbage forecasting, that includes dividing garbage into discrete categories for efficient recycling or disposal, is the main element of garbage management. One important garbage management project that aims to reduce environmental damage and encourage sustainable habits is garbage forecasting. emerging countries like India, where population growth and waste generation have become major problems. Nowadays, disposing of waste entails gathering trash from homes and businesses, dumping it in spacious backyards, and having employees sort through it by hand. It is a time consuming and inefficient procedure. As India's smart cities grow, a good waste management system must be implemented. This study intends to explore the use of modern trash photo categorization algorithms to automate garbage sorting into multiple categories. It does this by proposing a a convolutional neural network (CNN) based garbage categorization algorithm. The goal of this garbage classification system is to reduce the amount of manual labor required for waste separation while increasing the accuracy of waste sorting. The efficiency of waste management overall would be substantially increased by such a system. © 2025 IEEE.
Author Keywords	Automated Waste Sorting; Computer Vision; Convolutional Neural Networks (CNNs); Deep Learning; Garbage Classification; Image Classification; Image Processing; Machine Learning; Waste Management

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