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Dieser Artikel bietet einen Bericht über Entwicklungstendenzen und erste Erfahrungen virtueller Lernräume im Internet. Der Autor geht auf die Kommunikation im Internet, Lernräume im WWW, die Rollenverteilung im Lernraum ein, mit den Anforderungen aus Sicht der Lernenden, Lehrenden und der Verwaltung.
Dieser Artikel beleuchtet die Virtuelle Kooperative Hochschule (Organisation, Betreuung, Manpower), den Lernraum (Kommunikation im Internet, Lernräume im WWW und die Rollenverteilung im Lernraum), das Bundesleitprojekt Virtuelle Fachhochschule (Studentenleben, Projektdaten), Studieren im Netz (Medieninformatik, Virtuelles Lernmodul: Navigation), sowie die Didaktik.
In this paper, we present a method for detecting objects of interest, including cars, humans, and fire, in aerial images captured by unmanned aerial vehicles (UAVs) usually during vegetation fires. To achieve this, we use artificial neural networks and create a dataset for supervised learning. We accomplish the assisted labeling of the dataset through the implementation of an object detection pipeline that combines classic image processing techniques with pretrained neural networks. In addition, we develop a data augmentation pipeline to augment the dataset with utomatically labeled images. Finally, we evaluate the performance of different neural networks.
This paper reveals various approaches undertaken over more than two decades of teaching undergraduate programming classes at different Higher Education Institutions, in order to improve student activation and participation in class and consequently teaching and learning effectiveness.
While new technologies and the ubiquity of smartphones and internet access has brought new tools to the classroom and opened new didactic approaches, lessons learned from this personal long-term study show that neither technology itself nor any single new and often hyped didactic approach ensured sustained improvement of student activation. Rather it needs an integrated yet open approach towards a participative learning space supported but not created by new tools, technology and innovative teaching methods.
Technik des Online-Studiums
(2002)
Ziele und Konzepte der GI-Empfehlungen, Adressaten der Empfehlung, Studiengänge und Abschlussbezeichnungen, Ausbildungsziele und curriculare Anforderungen, Grundstruktur und Kategorien, Inhalte, Organisatorische Anforderungen, Qualität der Lehre, Ausstattung des Lehr- und Studienbetriebs, Akkreditierung.
In the realm of digital situational awareness during disaster situations, accurate digital representations,
like 3D models, play an indispensable role. To ensure the
safety of rescue teams, robotic platforms are often deployed
to generate these models. In this paper, we introduce an
innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces.
The video showcases a 3D model of a chemical company following a tank explosion that occurred on August 17, 2023, in Kempen computed with the AI algorithm Neural Radiance Field (NeRF). Captured by a compact mini drone measuring 18cm x 18cm and equipped with a 360° camera, these images offer an intricate perspective of the aftermath. After a comprehensive aerial survey and inspection of the 360° images taken within the facility, authorities confirmed that it was safe for the evacuated residents to return to their homes. See also:
https://www1.wdr.de/fernsehen/aktuelle-stunde/alle-videos/video-grosser-chemieunfall-in-kempen-100.html
Nerf(acto) for the 3D modeling of the Computer Science building of Westfälische Hochschule GE
(2023)
The video shows a very high resolution 3D point cloud !!! of the computer science building of the University of Applied Science Gelsenkirchen. For the recording a 3 minute flight with a M30T was performed. The 105 images taken by the wide-angle camera during this flight were localized within 3 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. Thus, a top 3D model is available after about 15 minutes.
The video shown here shows a free camera path rendered at 60 hz (Full HD).
The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD).