Classification of different types of plastics using Deep Transfer Learning

Chazhoor, Anthony Ashwin Peter, Zhu, Manli, Ho, Edmond S L., Gao, Bin and Woo, Wai Lok (2021) Classification of different types of plastics using Deep Transfer Learning. In: Proceedings of the International Conference on Robotics, Computer Vision and Intelligent Systems 2021: ROBOVIS 2021. SciTePress, Science and Technology Publications, Setúbal, Portugal. (In Press)

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Abstract

Plastic pollution has affected millions globally. Research shows tiny plastics in the food we eat, the water we drink, and even in the air, we breathe. An average human intakes 74,000 micro-plastic every year, which sig- nificantly affects the health of living beings. This pollution must be administered before it severely impacts the world. We have substantially compared three state-of-the-art models on the WaDaBa dataset, which contains different types of plastics. These models are capable of classifying different types of plastic wastes which can be reused or recycled, thus limiting their wastage.

Item Type: Book Section
Additional Information: 2nd International Conference on Robotics, Computer Vision and Intelligent Systems , ROBOVIS 2021 ; Conference date: 27-10-2021 Through 28-10-2021
Uncontrolled Keywords: Deep Learning, Transfer Learning, Image Classification, Recycling
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: John Coen
Date Deposited: 13 Sep 2021 14:34
Last Modified: 14 Sep 2021 13:16
URI: http://nrl.northumbria.ac.uk/id/eprint/47158

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