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3D Computer Vision for the Industrial Metaverse - On the potentials of Neural Radiance Fields
(2023)
The industrial metaverse refers to the use of virtual reality (VR) and augmented reality (AR) technologies in the context of industry and manufacturing. It is envisioned as a shared, immersive digital space where people can interact with and manipulate virtual representations of physical objects and processes. The industrial metaverse has the potential to transform the way products are designed, manufactured, and maintained,
enabling new levels of collaboration, automation, and innovation.
It further includes virtual representations of humans, also known as avatars. These avatars can be used to enable remote collaboration and communication between people in the virtual space. In this way, the industrial metaverse can facilitate virtual meetings, trainings, and other interactive experiences that involve human participants.
Neural Radiance Fields (NeRFs) are a powerful tool for synthesizing photorealistic images of 3D objects, including virtual representations of humans known as avatars. In this talk, we will discuss the potential applications of NeRFs in generating high-fidelity objects and avatars for use in the industrial metaverse.
Unter dem Motto „Technologie bewegt Pflege“ werden Beiträge aus Wissenschaft, Praxis und Industrie präsentiert. In einem abwechslungsreichen Programm werden aus verschiedenen Blickwinkeln die unterschiedlichen Schwerpunkte im Themenfeld Pflege und Technik diskutiert. Die Beiträge auf der 5. Clusterkonferenz, ausgerichtet vom Pflegepraxiszentrum Freiburg, sind im vorliegenden Abstractband ausgeführt.
The YOLO series of object detection algorithms, including YOLOv4 and YOLOv5, have shown superior performance in various medical diagnostic tasks, surpassing human ability in some cases. However, their black-box nature has limited their adoption in medical applications that require trust and explainability of model decisions. To address this issue, visual explanations for AI models, known as visual XAI, have been proposed in the form of heatmaps that highlight regions in the input that contributed most to a particular decision. Gradient-based approaches, such as Grad-CAM, and non-gradient-based approaches, such as Eigen-CAM, are applicable to YOLO models and do not require new layer implementation. This paper evaluates the performance of Grad-CAM and Eigen-CAM on the VinDrCXR Chest X-ray Abnormalities Detection dataset and discusses the limitations of these methods for explaining model decisions to data scientists.
Changes of human trunk circumferences during different breathing styles in different positions
(2023)
It is a fundamental right of every natural person to control which personal information is collected, stored and processed by whom, for what purposes and how long. In fact, many (cloud based) services can only be used if the user allows them broad data collection and analysis. Often, users can only decide to either give their data or not to participate in communities. The refusal to provide personal data results in significant drawbacks for social interaction. That is why we believe that there is a need for tools to control one's own data in an easy and effective way as protection against economic interest of global companies and their cloud computing systems (as data collector from apps, mobiles and services). Especially, as nowadays everybody is permanently online using different services and devices, users are often lacking the means to effectively control the access to their private data. Therefore, we present an approach to manage and distribute privacy settings: PRIVACY-AVARE is intended to enable users to centrally determine their data protection preferences and to apply them on different devices. Thus, users gain control over their data when using cloud based services. In this paper, we present the main idea of PRIVACY-AVARE.
Creating Interactive Experiences together with People with Dementia – an Inclusive Design Story
(2017)
Evaluation of high compliant elastomer balloons for the identification of artery biomechanics
(2023)
Führt die Omnipräsenz von Smartphone, Tablet & Co zu einer neuen Form des »Smart Social eLearning«?
(2016)
Ausgehend von dem Gedanken, dass das Medium Fernsehen in den letzten Jahren immer mehr durch das Internet als Leitmedium abgelöst wurde, wird in dem Beitrag eine Etablierung von SmartDevices im Unterricht diskutiert. Dabei wird aufgezeigt, dass die bisherige Entwicklung des Medieneinsatzes im Unterricht von multimedialen Lernprogrammen bis zu einem heutigen und zukünftigen „Smart Social eLearning“ reichen könnte, insbesondere durch den Einsatz der SmartDevices wie Tablets, Smartphones oder Smartwatches.
Darauf aufbauend werden die Ergebnisse einer empirischen Studie über den tatsächlichen Einsatz von und den Wunsch nach SmartDevices präsentiert. Dabei zeigte sich, dass der Großteil der Studierenden bereits SmartDevices zur Weiterbildung eingesetzt hat und auch bereits der Wunsch nach einem Einsatz dieser Geräte zur Weiterbildung besteht.