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OGC Testbed-15: Machine Learning Engineering Report
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| Definitionskos:definition | The Machine Learning (ML) Engineering Report (ER) documents the results of the ML thread in OGC Testbed-15. This thread explores the ability of ML to interact with and use OGC web standards in the context of natural resources applications. The thread includes five scenarios utilizing seven ML models in a solution architecture that includes implementations of the OGC Web Processing Service (WPS), Web Feature Service (WFS) and Catalogue Service for the Web (CSW) standards. This ER includes thorough investigation and documentation of the experiences of the thread participants. |
|---|---|
| Broaderbroader | Public Engineering Report |
| http://purl.org/dc/terms/createdcreated | 2019-12-20 |
| Creatorcreator | Sam Meek |
| seeAlsoseeAlso | https://docs.ogc.org/per/19-027r2.html |
| Statusstatus | valid |
| Notationnotation | 19-027r2 |
| Alternative LabelaltLabel | OGC Testbed-15: Machine Learning Engineering Report |
| 19-027r2 | |
| OGC document typedoctype | Public Engineering Report |