A Deep Learning Approach to Manage and Reduce Plastic Waste in the Oceans

Author:

El zaar Abdellah,Aoulalay Ayoub,Benaya Nabil,El mhouti Abderrahim,Massar Mohammed,El allati Abderrahim

Abstract

The accumulation of plastic objects in the Earth’s environment will adversely affect wildlife, wildlife habitat, and humans. The huge amount of unrecycled plastic ends up in landfill and thrown into unregulated dump sites. In many cases, specifically in the developing countries, plastic waste is thrown into rivers, streams and oceans. In this work, we employed the power of deep learning techniques in image processing and classification to recognize plastic waste. Our work aims to identify plastic texture and plastic objects in images in order to reduce plastic waste in the oceans, and facilitate waste management. For this, we use transfer learning in two ways: in the first one, a pre-trained CNN model on ImageNet is used as a feature extractor, then an SVM classifier for classification, the second strategy is based on fine tuning the pre-trained CNN model. Our approach was trained and tested using two (02) challenging datasets one is a texture recognition dataset and the other is for object detection, and achieves very satisfactory results using two (02) deep learning strategies.

Publisher

EDP Sciences

Subject

General Medicine

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The use of artificial intelligence algorithms to detect macroplastics in aquatic environments: A critical review;Science of The Total Environment;2024-10

2. Plastic Waste Identification Using Deep Learning for Adequate Waste Management;Journal of Artificial Intelligence and Capsule Networks;2024-06

3. Machine Learning based Object Detection to Protect Marine Ecosystem;2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA);2023-11-22

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