A Scalable AI Training Platform for Remote Sensing Data
| Autor: | Würz, Hendrik Martin, Kocon, Kevin, Pedretscher, Barbara, Klien, Eva, Eggeling, Eva |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
Branche: Bioeconomics and Infrastructure
Research Line: Machine learning (ML) Cloud computing Workflow management LTA: Scalable architectures for massive data sets LTA: Machine intelligence algorithms and data structures (incl. semantics) Remote sensing Artificial intelligence (AI) Branche: Information Technology |
| ISSN: | 2700-8150 |
| Popis: | We present a platform to support the AI development lifecycle with focus on large data like remote sensing.We target developers who are not allowed to use existing commercial cloud platforms for legal reasons or data compliance. The flexible implementation of our platform enables a deployment on classic server infrastructures as well as on internal clouds. Our goals of scalable and resource-efficient execution, independence from specific AI frameworks and programming languages, as well as reproducibility of results are met through a workflow-based calculation combined with the tool Data Version Control. The capabilities of the platform are demonstrated by training an AI-based forest type classification. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|