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Evaluation of Methods to Improve Synthetic Training Images for Semantic Segmentation of the Environment from UAV Perspective (Masterarbeit)

Rewatkar, Tushar Prakash (2024) Evaluation of Methods to Improve Synthetic Training Images for Semantic Segmentation of the Environment from UAV Perspective (Masterarbeit). DLR-Interner Bericht. DLR-IB-FT-BS-2024-126. Master's. Technische Hochschule Deggendorf.

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Item URL in elib:https://elib.dlr.de/206964/
Document Type:Monograph (DLR-Interner Bericht, Master's)
Title:Evaluation of Methods to Improve Synthetic Training Images for Semantic Segmentation of the Environment from UAV Perspective (Masterarbeit)
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Rewatkar, Tushar PrakashUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2024
Open Access:No
Status:Published
Keywords:Synthetic Data, Game Engine, Deep Learning, Image-to-Image Translation, Semantic Segmentation, Environment Perception, Unmanned Aerial Vehicle
Institution:Technische Hochschule Deggendorf
Department:Fakultät für Angewandte Informatik
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Components and Systems
DLR - Research area:Aeronautics
DLR - Program:L CS - Components and Systems
DLR - Research theme (Project):L - Unmanned Aerial Systems
Location: Braunschweig
Institutes and Institutions:Institute of Flight Systems > Unmanned Aircraft
Institute of Flight Systems
Deposited By: Rüter, Joachim
Deposited On:25 Nov 2024 16:38
Last Modified:25 Nov 2024 16:38

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