Self-Supervised Representation Learning for Geographical Data—A Systematic Literature Review
نویسندگان
چکیده
Self-supervised representation learning (SSRL) concerns the problem of a useful data without requirement for labelled or annotated data. This can, in turn, be used to support solutions downstream machine problems. SSRL has been demonstrated tool field geographical information science (GIS). In this article, we systematically review existing research literature space answer following five questions. What types representations were learnt? models used? problems solve? solve these problems? Finally, does using learnt improve overall performance?
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ژورنال
عنوان ژورنال: ISPRS international journal of geo-information
سال: 2023
ISSN: ['2220-9964']
DOI: https://doi.org/10.3390/ijgi12020064