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Detecting stranded macro-litter categories on drone orthophoto by a multi-class Neural Network

  • Published:2021-08 Issue: Volume:169 Page:112594
  • ISSN:0025-326X
  • Container-title:Marine Pollution Bulletin
  • language:en
  • Short-container-title:Marine Pollution Bulletin

Author:

Pinto Luis,Andriolo Umberto,Gonçalves Gil

Funder

Ministério da Ciência, Tecnologia e Ensino Superior

European Regional Development Fund

Fundação para a Ciência e a Tecnologia

Publisher

Elsevier BV

Subject

Pollution,Aquatic Science,Oceanography

Reference41 articles.

1. Accumulation of plastic waste during COVID-19;Adyel;Science.,2020

2. Mapping marine litter on coastal dunes with unmanned aerial systems: a showcase on the Atlantic Coast;Andriolo;Sci. Total Environ.,2020

3. Spatial and size distribution of macro-litter on coastal dunes from drone images: a case study on the Atlantic coast;Andriolo;Mar. Pollut. Bull.,2021

4. Drones for litter mapping: An inter-operator concordance test in marking beached items on aerial images;Andriolo;Mar. Pollut. Bull.,2021

5. Beach-dune morphodynamics and marine macro-litter abundance: an integrated approach with unmanned aerial system;Andriolo;Sci. Total Environ.,2020

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1. Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review;Remote Sensing;2024-01-23

2. Progress in Research on Marine Litter-Related Monitoring Technologies;Journal of Physics: Conference Series;2024-01-01

3. Using Multispectral UAV Imagery for Marine Debris Detection in Sri Lanka;2023 8th International Conference on Information Technology Research (ICITR);2023-12-07

4. Large-area automatic detection of shoreline stranded marine debris using deep learning;International Journal of Applied Earth Observation and Geoinformation;2023-11

5. Deep Learning-based drone acoustic event detection system for microphone arrays;Multimedia Tools and Applications;2023-10-31
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