Articles citing this article

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Cited article:

Overlapping bubble detection and tracking method based on convolutional Neural network and Kalman Filter

Daizhou Wen, Wuguang Chen, Junlian Yin, et al.
Chemical Engineering Science 263 118059 (2022)
https://doi.org/10.1016/j.ces.2022.118059

Automated Processing of Oceanic Bubble Images for Measuring Bubble Size Distributions underneath Breaking Waves

Raied S. Al-Lashi, Steve R. Gunn and Helen Czerski
Journal of Atmospheric and Oceanic Technology 33 (8) 1701 (2016)
https://doi.org/10.1175/JTECH-D-15-0222.1

Automated characterization and quantification of hydrocarbon seeps based on frontal illuminated video observations

J. Boelmann and O. Zielinski
Journal of the European Optical Society-Rapid Publications 10 15018 (2015)
https://doi.org/10.2971/jeos.2015.15018

Modelling the influence of oil content on optical properties of seawater in the Baltic Sea

K. Rudź, M. Darecki and H. Toczek
Journal of the European Optical Society-Rapid Publications 8 13063 (2013)
https://doi.org/10.2971/jeos.2013.13063

Automated gas bubble imaging at sea floor – a new method of in situ gas flux quantification

K. Thomanek, O. Zielinski, H. Sahling and G. Bohrmann
Ocean Science 6 (2) 549 (2010)
https://doi.org/10.5194/os-6-549-2010