A Method for Waste Segregation using Convolutional Neural Networks
- URL: http://arxiv.org/abs/2202.12258v1
- Date: Wed, 23 Feb 2022 14:32:10 GMT
- Title: A Method for Waste Segregation using Convolutional Neural Networks
- Authors: Jash Shah and Sagar Kamat
- Abstract summary: In this paper, we try to use deep learning algorithms to help solve this problem of waste classification.
Our proposed model achieves an accuracy of 94.9%.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Segregation of garbage is a primary concern in many nations across the world.
Even though we are 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, we try to
use deep learning algorithms 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.
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