ESIP
Browse
Hamed_ESIP_Summer_2019.pdf (21.23 MB)

Radiant ML Hub: A cloud based commons for geospatial training datasets

Download (21.23 MB)
presentation
posted on 2019-08-29, 12:02 authored by Hamed Alemohammad
A short presentation at the ESIP Summer Meeting 2019 in Tacoma Washington introducing Radiant MLHub as a public common for geospatial training datasets on the cloud.

History

Usage metrics

    ESIP Summer 2019

    Categories

    Keywords

    Remote SensingMachine LearningTraining DataESIP Summer 2019Earth ObservationsSTACRadiant MLHubMLHubKnowledge Representation and Machine LearningPhotogrammetry and Remote SensingArtificial Intelligence and Image Processing

    Licence

    CC BY 4.0

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC