Identification of Baikal phytoplankton inferred from computer vision methods and machine learning
- Authors: Lysenko А.V.1,2, Oznobikhin М.S.1,2, Kireev Е.А.1,2, Dubrova K.S.1, Vorobyeva S.S.1
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Affiliations:
- Limnological Institute, Siberian Branch of the Russian Academy of Sciences
- Irkutsk State University
- Issue: No 3 (2021)
- Pages: 1143-1146
- Section: Articles
- URL: https://journals.rcsi.science/2658-3518/article/view/285014
- ID: 285014
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Abstract
This study discusses the problem of phytoplankton classification using computer vision methods and convolutional neural networks. We created a system for automatic object recognition consisting of two parts: analysis and primary processing of phytoplankton images and development of the neural network based on the obtained information about the images. We developed software that can detect particular objects in images from a light microscope. We trained a convolutional neural network in transfer learning and determined optimal parameters of this neural network and the optimal size of using dataset. To increase accuracy for these groups of classes, we created three neural networks with the same structure. The obtained accuracy in the classification of Baikal phytoplankton by these neural networks was up to 80%.
About the authors
А. V. Lysenko
Limnological Institute, Siberian Branch of the Russian Academy of Sciences; Irkutsk State University
Author for correspondence.
Email: allessouth@gmail.com
Institute of Mathematics and Information Technologies
Russian Federation, 664033, Irkutsk, Ulan-Batorskaya str., 3; 664003, Irkutsk, Gagarina str., 20М. S. Oznobikhin
Limnological Institute, Siberian Branch of the Russian Academy of Sciences; Irkutsk State University
Email: allessouth@gmail.com
Institute of Mathematics and Information Technologies
Russian Federation, 664033, Irkutsk, Ulan-Batorskaya str., 3; 664003, Irkutsk, Gagarina str., 20Е. А. Kireev
Limnological Institute, Siberian Branch of the Russian Academy of Sciences; Irkutsk State University
Email: allessouth@gmail.com
Institute of Mathematics and Information Technologies
Russian Federation, 664033, Irkutsk, Ulan-Batorskaya str., 3; 664003, Irkutsk, Gagarina str., 20K. S. Dubrova
Limnological Institute, Siberian Branch of the Russian Academy of Sciences
Email: allessouth@gmail.com
Russian Federation, 664033, Irkutsk, Ulan-Batorskaya str., 3
S. S. Vorobyeva
Limnological Institute, Siberian Branch of the Russian Academy of Sciences
Email: allessouth@gmail.com
Russian Federation, 664033, Irkutsk, Ulan-Batorskaya str., 3
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