https://doi.org/10.25678/000BJ0
Aquascope October 2022
Dataset extent
Data and Resources
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class_and_feat_0p5xMAG_oct2022.tar.gzTAR
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images_0p5xMAG_oct2022.tar.gzTAR
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class_and_feat_5p0xMAG_oct2022.tar.gzTAR
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images_5p0xMAG_oct2022.tar.gzTAR
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README.txtTXT
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raw_data_5p0xMAG_oct2022.tar.gzTAR
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raw_data_0p5xMAG_oct2022_1-7.tar.gzTAR
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raw_data_0p5xMAG_oct2022_08.tar.gzTAR
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raw_data_0p5xMAG_oct2022_09.tar.gzTAR
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raw_data_0p5xMAG_oct2022_10.tar.gzTAR
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raw_data_0p5xMAG_oct2022_11.tar.gzTAR
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raw_data_0p5xMAG_oct2022_12.tar.gzTAR
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raw_data_0p5xMAG_oct2022_13-14.tar.gzTAR
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raw_data_0p5xMAG_oct2022_15.tar.gzTAR
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raw_data_0p5xMAG_oct2022_16.tar.gzTAR
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raw_data_0p5xMAG_oct2022_17.tar.gzTAR
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raw_data_0p5xMAG_oct2022_18.tar.gzTAR
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raw_data_0p5xMAG_oct2022_19.tar.gzTAR
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raw_data_0p5xMAG_oct2022_20.tar.gzTAR
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raw_data_0p5xMAG_oct2022_21-23.tar.gzTAR
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raw_data_0p5xMAG_oct2022_24a.tar.gzTAR
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raw_data_0p5xMAG_oct2022_24b.tar.gzTAR
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raw_data_0p5xMAG_oct2022_25.tar.gzTAR
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raw_data_0p5xMAG_oct2022_26.tar.gzTAR
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raw_data_0p5xMAG_oct2022_27.tar.gzTAR
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raw_data_0p5xMAG_oct2022_28.tar.gzTAR
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raw_data_0p5xMAG_oct2022_29.tar.gzTAR
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raw_data_0p5xMAG_oct2022_30.tar.gzTAR
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raw_data_0p5xMAG_oct2022_31a.tar.gzTAR
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raw_data_0p5xMAG_oct2022_31b.tar.gzTAR
Citation
Dennis, S., Merz, E., Reyes, M., Merkli, S., Baity Jesi, M., Kyathanahally, S., et al. (2023). Aquascope October 2022 (Version 1.0). Eawag: Swiss Federal Institute of Aquatic Science and Technology. https://doi.org/10.25678/000BJ0
Metadata
Author |
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Keywords | phytoplankton images,zooplankton images,plankton classification,machine learning,time series,image features,plankton communities |
Taxa (scientific names) |
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Organisms (generic terms) |
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Timerange |
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Geographic Name(s) |
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Review Level | domain specific |
Curator | Dennis, Stuart |
Contact | Pomati, Francesco <Francesco.Pomati@eawag.ch> |
DOI | 10.25678/000BJ0 |