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661 to 670 of 679 Results
MS Excel Spreadsheet - 638.7 KB - MD5: c97c0e9ca45ceb8c0278686ce183877f
Data
Consumption of cowpea-based dishes by adult population in 2 rural areas of South Benin
Tabular Data - 563.6 KB - 248 Variables, 642 Observations - UNF:6:nMrwxB1OzYagKTXtIzdmfw==
Data
Consumption of cowpea-based dishes by adult population in urban areas of South Benin (Cotonou)
Feb 14, 2023 - UMR ESPACE-DEV
Bonnet, Marie-Paule; Garnier, Jérémie; Da Motta Marques, David; Seyler, Patrick; Dias-Roque, Derlayne Flávia; Nunes Kraus, Cleber, 2023, "Surface water quality (2013-2017) - Curuai floodplain, Brazil, Pará", https://doi.org/10.23708/SNGQHV, DataSuds, V1, UNF:6:ANjAoi1b+71R2DZt5Euwew== [fileUNF]
This dataset was acquired within the framework of several successive French-Brazilian projects with the objective of characterizing the spatio-temporal variations of water quality in the Curuai floodplain. It includes data that were acquired between March 2013 and September 2017...
Tabular Data - 3.0 KB - 3 Variables, 42 Observations - UNF:6:AgzmMagFbRYXBsRhoxX41Q==
Documentation
Some informations on headers used in LMIOCE_WQ_Curuai_Floodplain_sampledata.csv
Tabular Data - 697.6 KB - 1 Variables, 8323 Observations - UNF:6:VteW2Ah2s5WCuBDt09GYrw==
Data
Physico-chemical vertical profiles
Tabular Data - 127.1 KB - 42 Variables, 396 Observations - UNF:6:dwY+3qWii4CApl9i3YjTZg==
Data
Water quality data from water samples collected at surface and for some of the stations, at several depths
Jan 13, 2023 - UMI UMMISCO
Bayet, Theophile, 2023, "COCO-style geographically unbiased image dataset for computer vision applications", https://doi.org/10.23708/N2UY4C, DataSuds, V1
There are already a lot of datasets linked to computer vision tasks (Imagenet, MS COCO, Pascal VOC, OpenImages, and numerous others), but they all suffer from important bias. One bias of significance for us is the data origin: most datasets are composed of data coming from develo...
ZIP Archive - 301.2 KB - MD5: 7d00b44bfd43f82760b0d1500f661c5e
Data
Annotations for 400 images per geographic zones, JSON format (COCO-style): presence or absence of 91 categories of objects or concepts on the images.
Adobe PDF - 55.9 KB - MD5: 808d3cb240f0b589e1ae55e03294151c
Documentation
Data Management Plan of the project, in French (6 pages)
ZIP Archive - 168.1 MB - MD5: b3467eebbefb50907f880809a97fb8df
Data
23 text files: comma separated URLs for each of the 23 geographic zones. Files are named according to geographic zones (UN M49 standard)
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