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A Method for Waste Segregation using Convolutional Neural Networks

Jash Shah, Sagar Kamat

20222022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)25 citationsDOI

Abstract

Segregation of garbage is a primary concern in many nations across the world. In spite of being in the modern era, many people still do not know how to distinguish between organic and recyclable waste. It is because of this that the world is facing a major crisis of waste disposal. In this paper, deep learning algorithms have been used to help solve this problem of waste classification. The waste is classified into two categories like organic and recyclable. Our proposed model achieves an accuracy of 94.9%. Although the other two models also show promising results, the Proposed Model stands out with the greatest accuracy. With the help of deep learning, one of the greatest obstacles to efficient waste management can finally be removed.

Topics & Concepts

GarbageConvolutional neural networkDeep learningComputer scienceArtificial neural networkArtificial intelligenceBiodegradable wasteWaste managementMachine learningEngineeringMunicipal Solid Waste ManagementAdvanced Neural Network ApplicationsElectricity Theft Detection Techniques
A Method for Waste Segregation using Convolutional Neural Networks | Litcius