Acta Marisiensis.
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Year 2024
Volume 21 (XXXVIII), no 1 Year 2023 Volume 20 (XXXVII), no 1 Volume 20 (XXXVII), no 2 Year 2022 Volume 19 (XXXVI), no 1 Volume 19 (XXXVI), no 2 Year 2021 Volume 18 (XXXV), no 1 Volume 18 (XXXV), no 2 Year 2020 Volume 17 (XXXIV), no 1 Volume 17 (XXXIV), no 2 Year 2019 Volume 16 (XXXIII), no 1 Volume 16 (XXXIII), no 2 Year 2018 Volume 15 (XXXII), no 1 Volume 15 (XXXII), no 2 Year 2017 Volume 14 (XXXI), no 1 Volume 14 (XXXI), no 2 Year 2016 Volume 13 (XXX), no 1 Volume 13 (XXX), no 2 Year 2015 Volume 12 (XXIX), no 1 Volume 12 (XXIX), no 2 Year 2014 Volume 11 (XXVIII), no 1 Volume 11 (XXVIII), no 2 Year 2013 Volume 10 (XXVII), no 1 Volume 10 (XXVII), no 2 Year 2012 Volume 9 (XXVI), no 1 Volume 9 (XXVI), no 2 Year 2011 Volume 8 (XXV), no 1 Volume 8 (XXV), no 2 Year 2010 Volume 7 (XXIV), no 1 Volume 7 (XXIV), no 2 Year 2009 Volume 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 View full article |
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Update: 19-Jun-2024 | © Published by University Press |