A Study on the Monitoring of Floating Marine Macro-Litter Using a Multi-Spectral Sensor and Classification Based on Deep Learning

A Study on the Monitoring of Floating Marine Macro-Litter Using a Multi-Spectral Sensor and Classification Based on Deep Learning

Increasing global plastic usage has raised critical concerns regarding marine pollution. This study addresses the pressing issue of floating marine macro-litter (FMML) by developing a novel monitoring system using a multi-spectral sensor and drones along the southern coast of South Korea. Subsequent...

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Bibliographic Details
Main Authors: Youchul Jeong, Jisun Shin, Jong-Seok Lee, Ji-Yeon Baek, Daniel Schläpfer, Sin-Young Kim, Jin-Yong Jeong, Young-Heon Jo
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
Subjects:
floating marine macro-litter
unmanned aerial vehicle
multi-spectral sensor
atmospheric correction
reflectance retrieval
convolutional neural network
Online Access:https://www.mdpi.com/2072-4292/16/23/4347
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https://www.mdpi.com/2072-4292/16/23/4347

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