Self-Supervised Image Classification [dataset]

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This collection contains data and models for the Self-Supervised Classification workflow. Further information, and Python code, can be found in this GitHub repository: https://github.com/geojames/Self-Supervised-Classification

Resource type: Dataset
Contributors: Creator: Carbonneau, Patrice ¹
Data collector: Dugdale, Steve ²
Data collector: Miyamoto, Hitoshi ³
Data collector: Woodget, Amy ⁴
Data collector: Fonstad, Mark ⁵
Data collector: Dietrich, James ⁶
Data collector: Breckon, Toby ⁷

¹ Durham University, UK
² Nottingham University, UK
³ Shibaura Institute of Tech., Japan
⁴ Loughborough University, UK
⁵ University of Oregon
⁶ University of Northern Iowa
⁷ Durham University
Funder: GEOSALAR project
NSERC/CRSNG HydroNet Strategic Network
AMBER, EU horizon 2020 program
University or Worcester
Japanese Society for the Promotion of Science
National Science Foundation
British Society for Geomorphology
Tokyo foundation
University of Oregon
Research methods: Deep Learning and Machine Learning
Other description
Keyword: Deep Learning
Land-cover classification
Machine Learning
Hyperspatial Imagery
UAV imagery
Airborne imagery
Fluvial Remote Sensing
Subject: Deep Learning
Location
Language
Cited in
Identifier: ark:/32150/r2j67313813
doi:10.15128/r2j67313813
Rights: Creative Commons Attribution 4.0 International (CC BY)
Publisher: Durham University
Date Created

Depositor: N. Syrotiuk
Date Uploaded: 5 June 2019, 13:06:20
Date Modified: 17 June 2019, 10:06:03
Audit Status: Audits have not yet been run on this file.
Characterization: File format: zip (ZIP Format)

Mime type: application/zip

File size: 4768753086

Last modified: 2019:06:17 10:56:54+01:00

Filename: ResearchData.zip

Original checksum: e0d8a5a07f2dc5be665228af57e1b8a0

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