Acta Marisiensis.
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Anul 2024
Volum 21 (XXXVIII), nr 1 Volum 21 (XXXVIII), nr 2 Anul 2023 Volum 20 (XXXVII), nr 1 Volum 20 (XXXVII), nr 2 Anul 2022 Volum 19 (XXXVI), nr 1 Volum 19 (XXXVI), nr 2 Anul 2021 Volum 18 (XXXV), nr 1 Volum 18 (XXXV), nr 2 Anul 2020 Volum 17 (XXXIV), nr 1 Volum 17 (XXXIV), nr 2 Anul 2019 Volum 16 (XXXIII), nr 1 Volum 16 (XXXIII), nr 2 Anul 2018 Volum 15 (XXXII), nr 1 Volum 15 (XXXII), nr 2 Anul 2017 Volum 14 (XXXI), nr 1 Volum 14 (XXXI), nr 2 Anul 2016 Volum 13 (XXX), nr 1 Volum 13 (XXX), nr 2 Anul 2015 Volum 12 (XXIX), nr 1 Volum 12 (XXIX), nr 2 Anul 2014 Volum 11 (XXVIII), nr 1 Volum 11 (XXVIII), nr 2 Anul 2013 Volum 10 (XXVII), nr 1 Volum 10 (XXVII), nr 2 Anul 2012 Volum 9 (XXVI), nr 1 Volum 9 (XXVI), nr 2 Anul 2011 Volum 8 (XXV), nr 1 Volum 8 (XXV), nr 2 Anul 2010 Volum 7 (XXIV), nr 1 Volum 7 (XXIV), nr 2 Anul 2009 Volum 6 (XXIII) |
2022, Volume 19 (XXXVI), no 1
Ornelta GOXHAJ, Nilay Gul YILMAZ, Istanbul Technical University, Turkey Lida KOUHALVANDI, Dogus University, Turkey Ibraheem SHAYEA, Istanbul Technical University, Turkey Azızul AZIZAN, Universiti Teknologi, Malaysia Abstract: Serious problems are on the rise, especially in these current times. The world is facing too many environmental threats. Water pollution is one of the main issues threatening the future. In some parts of the world, the water’s surface is covered by mucilage, which is dangerous for both aquatic animals and humans. This article firstly defines mucilage and highlights the reasons for its production. Afterwards to tackle water pollution, cleaning systems using image detection with the help of machine learning supervised classification algorithms are highlighted. This paper showcases the machine learning and classification used as well as the best solution for convolutional neural network and regionbased convolutional neural network methods. DOI: https://doi.org/10.2478/amset-2022-0006 Pages: 28-35 Cite as: download info as bibtex View full article |
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Update: 18-Dec-2024 | © Published by University Press |