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Publication Year: 2023

681 to 690 of 693 Results

COCO-style geographically unbiased image dataset for computer vision applications 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...
COCO_World_URLs_Annotations.zip Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications 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.
COCO_World_URLs_Data_Management_Plan.pdf Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications Adobe PDF - 55.9 KB - MD5: 808d3cb240f0b589e1ae55e03294151c Documentation Data Management Plan of the project, in French (6 pages)
COCO_World_URLs_Data.zip Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications 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)
COCO_World_URLs_Description.pdf Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications Adobe PDF - 81.4 KB - MD5: 0e8500cc3f9e2060ccc0bd6ca8c99986 Documentation Detailed description of the dataset, in English
COCO_World_URLs_Licenses.zip Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications ZIP Archive - 213.9 KB - MD5: 4288be6f0763234a9becf9bd6f10d2f4 Data Licenses for the 400 annotations per geographic zones (based on the original licenses specified per image), CSV format.
COCO_World_URLs_Readme.txt Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications Plain Text - 1.7 KB - MD5: adddf89525947a701c5725394ff712fb Documentation Dataset citation and summary
Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger Jan 4, 2023 - UMR iEES-Paris Mahuzier, C.; Bodo, B.S; Maman Sani, A.; Hamissou, A.C, 2023, "Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger", https://doi.org/10.23708/JQK9E6, DataSuds, V1 This dataset was acquired using the combination of Sentinel-1 radar and Sentinel-2 optical image time series with indices (BI2, NDVI, MSAVI2, NDII). A total of 112 sentinel images were acquired in 2021 allowing a coherent and reliable mapping of land use in relation to the croppi...
areas.ods Jan 4, 2023 - Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger OpenOffice Spreadsheet - 3.9 KB - MD5: 8e23d0e46aaba67679233f8cb36f0fe2 calculation of areas in ha for each class
Land_cover_Maradi_2021_10m_7class.png Jan 4, 2023 - Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger PNG Image - 1.2 MB - MD5: abea5be7bc1b9699b4eaf3f0f762a37d Quicklook

COCO-style geographically unbiased image dataset for computer vision applications

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...

COCO_World_URLs_Annotations.zip

Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications

ZIP Archive - 301.2 KB -

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.

COCO_World_URLs_Data_Management_Plan.pdf

Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications

Adobe PDF - 55.9 KB -

Documentation

Data Management Plan of the project, in French (6 pages)

COCO_World_URLs_Data.zip

Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications

ZIP Archive - 168.1 MB -

Data

23 text files: comma separated URLs for each of the 23 geographic zones. Files are named according to geographic zones (UN M49 standard)

COCO_World_URLs_Description.pdf

Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications

Adobe PDF - 81.4 KB -

Documentation

Detailed description of the dataset, in English

COCO_World_URLs_Licenses.zip

Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications

ZIP Archive - 213.9 KB -

Data

Licenses for the 400 annotations per geographic zones (based on the original licenses specified per image), CSV format.

COCO_World_URLs_Readme.txt

Jan 13, 2023 - COCO-style geographically unbiased image dataset for computer vision applications

Plain Text - 1.7 KB -

Documentation

Dataset citation and summary

Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger

Jan 4, 2023 - UMR iEES-Paris

Mahuzier, C.; Bodo, B.S; Maman Sani, A.; Hamissou, A.C, 2023, "Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger", https://doi.org/10.23708/JQK9E6, DataSuds, V1

This dataset was acquired using the combination of Sentinel-1 radar and Sentinel-2 optical image time series with indices (BI2, NDVI, MSAVI2, NDII). A total of 112 sentinel images were acquired in 2021 allowing a coherent and reliable mapping of land use in relation to the croppi...

areas.ods

Jan 4, 2023 - Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger

OpenOffice Spreadsheet - 3.9 KB -

calculation of areas in ha for each class

Land_cover_Maradi_2021_10m_7class.png

Jan 4, 2023 - Random Forest classification of land cover from Sentinel satellite images in 2021 for the Agro2Ecos project area, Maradi, Niger

PNG Image - 1.2 MB -

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