Application of Computer Vision Techniques for Segregation of
PlasticWaste based on Resin Identification Code
- URL: http://arxiv.org/abs/2011.07747v1
- Date: Mon, 16 Nov 2020 06:50:32 GMT
- Title: Application of Computer Vision Techniques for Segregation of
PlasticWaste based on Resin Identification Code
- Authors: Shivaank Agarwal, Ravindra Gudi, Paresh Saxena
- Abstract summary: We propose the design, training and testing of different machine learning techniques to identify plastic waste.
Our proposed approach does not require any augmentation to increase the size of the database and achieved a high accuracy of 99.74%.
- Score: 0.8103046443444949
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This paper presents methods to identify the plastic waste based on its resin
identification code to provide an efficient recycling of post-consumer plastic
waste. We propose the design, training and testing of different machine
learning techniques to (i) identify a plastic waste that belongs to the known
categories of plastic waste when the system is trained and (ii) identify a new
plastic waste that do not belong the any known categories of plastic waste
while the system is trained. For the first case,we propose the use of one-shot
learning techniques using Siamese and Triplet loss networks. Our proposed
approach does not require any augmentation to increase the size of the database
and achieved a high accuracy of 99.74%. For the second case, we propose the use
of supervised and unsupervised dimensionality reduction techniques and achieved
an accuracy of 95% to correctly identify a new plastic waste.
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