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Investigating Unsupervised Domain Adaptation for Synthetic Data for ML-Based UAV Environment Perception (Bachelorarbeit)

Grapenthin, Jan (2024) Investigating Unsupervised Domain Adaptation for Synthetic Data for ML-Based UAV Environment Perception (Bachelorarbeit). DLR-Interner Bericht. DLR-IB-FT-BS-2024-11. Bachelor's.

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Item URL in elib:https://elib.dlr.de/202903/
Document Type:Monograph (DLR-Interner Bericht, Bachelor's)
Title:Investigating Unsupervised Domain Adaptation for Synthetic Data for ML-Based UAV Environment Perception (Bachelorarbeit)
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Grapenthin, JanFT-ULFUNSPECIFIEDUNSPECIFIED
Date:2024
Open Access:No
Status:Published
Keywords:Synthetic Data; Unsupervised Domain Adaptation; Adversarial Training; Unmanned Aerial Vehicle (UAV)
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:Digitalisation
DLR - Program:D IAS - Innovative Autonomous Systems
DLR - Research theme (Project):D - SKIAS
Location: Braunschweig
Institutes and Institutions:Institute of Flight Systems > Unmanned Aircraft
Institute of Flight Systems
Deposited By: Rüter, Joachim
Deposited On:21 Feb 2024 15:48
Last Modified:21 Feb 2024 15:48

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