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Salisch, Timo (2023) Introduction to Automated Classification of Remote Sensing Data using Airborne LiDAR Measurements. Project Report. Project thesis. Duale Hochschule Baden-Wuerttemberg (DHBW). 8 S.
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Abstract
AutoGeoLabel, a method for automatically creating labels for geospatial data, is explained together with an example usage of it. By applying rules to e.g. statistical features of data, AutoGeoLabel can create segmentation maps of unclassified data. It is furthermore demonstrated and evaluated using LiDAR data. Additionally, the benefit of using morphological filters with AutoGeoLabel is shown and a simple approach for finding fitting parameters for these filters is mentioned.
| Item URL in elib: | https://elib.dlr.de/195160/ | ||||||||
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| Document Type: | Monograph (Project Report, Project thesis) | ||||||||
| Additional Information: | project supervision: Conrad.Albrecht@DLR.de | ||||||||
| Title: | Introduction to Automated Classification of Remote Sensing Data using Airborne LiDAR Measurements | ||||||||
| Authors: |
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| Date: | 18 May 2023 | ||||||||
| Refereed publication: | No | ||||||||
| Open Access: | No | ||||||||
| Gold Open Access: | No | ||||||||
| In SCOPUS: | No | ||||||||
| In ISI Web of Science: | No | ||||||||
| Number of Pages: | 8 | ||||||||
| Status: | Published | ||||||||
| Keywords: | LiDAR, urban mapping, noisy geospatial annotation, computer vision | ||||||||
| Institution: | Duale Hochschule Baden-Wuerttemberg (DHBW) | ||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||
| HGF - Program: | Space | ||||||||
| HGF - Program Themes: | Earth Observation | ||||||||
| DLR - Research area: | Raumfahrt | ||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||
| DLR - Research theme (Project): | R - LIDAR research and development, D - urbanModel, R - Artificial Intelligence | ||||||||
| Location: | Oberpfaffenhofen | ||||||||
| Institutes and Institutions: | Remote Sensing Technology Institute > EO Data Science | ||||||||
| Deposited By: | Albrecht, Conrad M | ||||||||
| Deposited On: | 22 May 2023 13:40 | ||||||||
| Last Modified: | 22 May 2023 17:00 |
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