University of Twente Student Theses
Supervised contrastive learning to overcome inconsistencies in exhaled breath data
Lucas, R.H. (2022) Supervised contrastive learning to overcome inconsistencies in exhaled breath data.
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Full Text Status: | Access to this publication is restricted |
Embargo date: | 31 August 2024 |
Item Type: | Essay (Master) |
Clients: | The eNose Company, Zutphen, The Netherlands |
Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
Subject: | 54 computer science |
Programme: | Computer Science MSc (60300) |
Link to this item: | https://purl.utwente.nl/essays/92848 |
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