Publikationen

Enhancing Drone Operation Efficiency and Operator Experience: Integrating Extended Reality and Adaptive Systems with Situation-Aware Models

Bendig, H. . (2024). Enhancing Drone Operation Efficiency and Operator Experience: Integrating Extended Reality and Adaptive Systems with Situation-Aware Models. Mensch und Computer 2024. Karlsruhe, Germany: Gesellschaft für Informatik e.V. http://doi.org/10.18420/muc2024-mci-dc-178 (Original work published September 2024)

Abstract

This research project investigates how adaptive Augmented Reality (AR) applications can improve the efficiency of drone operations and the experience of operators. Drones, particularly Unmanned Aerial Vehicles (UAVs), are increasingly employed in search and rescue (SAR) missions due to their rapid deployment capabilities and the ability to access hazardous areas or viewpoints that are otherwise unreachable. Operating drones in these high-demanding scenarios requires operators to possess certain cognitive abilities to manage the UAV effectively. Our research aims to develop a situation-aware interaction model that considers data from the task, the UAVs, and the human operator, offering support during demanding missions or low abilities. This model will be integrated into an AR application designed to adjust to the current situation, thereby enhancing operational outcomes and user experience.
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- Personenseiten
  
  Bendig, Henner
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
  
  UsabilityLab
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
  
  Data Science und Künstliche Intelligenz
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Enhancing Drone Operation Efficiency and Operator Experience: Integrating Extended Reality and Adaptive Systems with Situation-Aware Models

Bendig, H. . (2024). Enhancing Drone Operation Efficiency and Operator Experience: Integrating Extended Reality and Adaptive Systems with Situation-Aware Models. Mensch und Computer 2024. Karlsruhe, Germany: Gesellschaft für Informatik e.V. http://doi.org/10.18420/muc2024-mci-dc-178 (Original work published September 2024)

Abstract

This research project investigates how adaptive Augmented Reality (AR) applications can improve the efficiency of drone operations and the experience of operators. Drones, particularly Unmanned Aerial Vehicles (UAVs), are increasingly employed in search and rescue (SAR) missions due to their rapid deployment capabilities and the ability to access hazardous areas or viewpoints that are otherwise unreachable. Operating drones in these high-demanding scenarios requires operators to possess certain cognitive abilities to manage the UAV effectively. Our research aims to develop a situation-aware interaction model that considers data from the task, the UAVs, and the human operator, offering support during demanding missions or low abilities. This model will be integrated into an AR application designed to adjust to the current situation, thereby enhancing operational outcomes and user experience.
- Suche auf Google Scholar
- DOI Verweis
Exportformate
Weiterführende Links
- Personenseiten
  
  Bendig, Henner
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
  
  UsabilityLab
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
  
  Data Science und Künstliche Intelligenz
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Enhancing Spatial Problem-Solving Through Data-Driven Methods: A Practical Approach Utilizing Immersive Technologies and Multimodal Physical Tracking

Bendig, H. . (2024). Enhancing Spatial Problem-Solving Through Data-Driven Methods: A Practical Approach Utilizing Immersive Technologies and Multimodal Physical Tracking. In Companion Proceedings of the 29th International Conference on Intelligent User Interfaces (S. 150–152). Greenville, SC, USA: Association for Computing Machinery. http://doi.org/10.1145/3640544.3645244 (Original work published März 2024)

Abstract

This project aims to explore how data-driven methods can be used to enhance humans’ problem-solving skills in spatial tasks and how they can be integrated into immersive tutoring systems. The goal is to provide an enhanced, state-dependent approach that is also applicable outside the laboratory, within real-life scenarios. Digital tutoring and learning systems are typically expert systems and follow a predefined training routine. Ongoing research concentrates on adaptive methods within affective- and cognition-aware systems, yet there is comparatively less investigation into recognizing and adapting problem-solving strategies. Spatial skill have been shown to be especially important for STEM (Science, Technology, Engineering, Mathematics) disciplines in general. Due to their design, immersive systems are particularly suitable for training of spatial skills and are thus frequently utilized for this.
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- Personenseiten
  
  Bendig, Henner
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
  
  UsabilityLab
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
  
  Data Science und Künstliche Intelligenz
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Enhancing Spatial Problem-Solving Through Data-Driven Methods: A Practical Approach Utilizing Immersive Technologies and Multimodal Physical Tracking

Bendig, H. . (2024). Enhancing Spatial Problem-Solving Through Data-Driven Methods: A Practical Approach Utilizing Immersive Technologies and Multimodal Physical Tracking. In Companion Proceedings of the 29th International Conference on Intelligent User Interfaces (S. 150–152). Greenville, SC, USA: Association for Computing Machinery. http://doi.org/10.1145/3640544.3645244 (Original work published März 2024)

Abstract

This project aims to explore how data-driven methods can be used to enhance humans’ problem-solving skills in spatial tasks and how they can be integrated into immersive tutoring systems. The goal is to provide an enhanced, state-dependent approach that is also applicable outside the laboratory, within real-life scenarios. Digital tutoring and learning systems are typically expert systems and follow a predefined training routine. Ongoing research concentrates on adaptive methods within affective- and cognition-aware systems, yet there is comparatively less investigation into recognizing and adapting problem-solving strategies. Spatial skill have been shown to be especially important for STEM (Science, Technology, Engineering, Mathematics) disciplines in general. Due to their design, immersive systems are particularly suitable for training of spatial skills and are thus frequently utilized for this.
- Suche auf Google Scholar
- DOI Verweis
Exportformate
Weiterführende Links
- Personenseiten
  
  Bendig, Henner
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
  
  UsabilityLab
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
  
  Data Science und Künstliche Intelligenz
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Training for Ultrasound Imaging: An Evaluation of SonoGame

Gürgan, S. ., Henze, V. ., Gall, C. ., Schoenfisch, B. ., Brucker, S. ., Hahn, M. ., … Teistler, M. . (2024). Training for Ultrasound Imaging: An Evaluation of SonoGame. ACM Symposium on Spatial User Interaction (SUI 2024). Trier, Germany: ACM, New York. http://doi.org/10.1145/3677386.3688880
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- DOI Verweis
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Weiterführende Links
- Personenseiten
  
  Bertel, Sven
  
  Teistler, Michael
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Problem Solving Strategies in Physical and Mental Rotation

Wetzel, S. ., & Bertel, S. . (2024). Problem Solving Strategies in Physical and Mental Rotation. Spatial Cognition Conference 2024. Dublin.
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- Personenseiten
  
  Bertel, Sven
- Forschungsprojekt
  
  Kompetenzen für eine digitale Welt: partizipative Entwicklung von Apps zum Training räumlicher Fähigkeiten im Unterricht
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis

Ganz, J. ., Marzahl, C. ., Ammeling, J. ., Rosbach, E. ., Richter, B. ., Puget, C. ., … Aubreville, M. . (2024). Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis. Scientific Reports, 14, 26273. http://doi.org/10.1038/s41598-024-77244-6

Abstract

Abstract The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation. Furthermore, label noise introduced during the annotation process may impede the algorithms’ performance. Unlike H&E, where identification of MFs is based mainly on morphological features, the mitosis-specific antibody phospho-histone H3 (PHH3) specifically highlights MFs. Counting MFs on slides stained against PHH3 leads to higher agreement among raters and has therefore recently been used as a ground truth for the annotation of MFs in H&E. However, as PHH3 facilitates the recognition of cells indistinguishable from H&E staining alone, the use of this ground truth could potentially introduce an interpretation shift and even label noise into the H&E-related dataset, impacting model performance. This study analyzes the impact of PHH3-assisted MF annotation on inter-rater reliability and object level agreement through an extensive multi-rater experiment. Subsequently, MF detectors, including a novel dual-stain detector, were evaluated on the resulting datasets to investigate the influence of PHH3-assisted labeling on the models’ performance. We found that the annotators’ object-level agreement significantly increased when using PHH3-assisted labeling (F1: 0.53 to 0.74). However, this enhancement in label consistency did not translate to improved performance for H&E-based detectors, neither during the training phase nor the evaluation phase. Conversely, the dual-stain detector was able to benefit from the higher consistency. This reveals an information mismatch between the H&E and PHH3-stained images as the cause of this effect, which renders PHH3-assisted annotations not well-aligned for use with H&E-based detectors. Based on our findings, we propose an improved PHH3-assisted labeling procedure.
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- Personenseiten
  
  Aubreville, Marc
- Forschungsprojekt
  
  Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence
- Abteilung/Einrichtung
  
  FLAIR - Flensburg Artificial Intelligence Research
  
  CIVU – Center for Interaction, Visualization and Usability
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
  
  Data Science und Künstliche Intelligenz
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Data-Driven Analysis of Physical and Mental Rotation Strategies

Wetzel, S. ., & Bertel, S. . (2024). Data-Driven Analysis of Physical and Mental Rotation Strategies. CogSci 2025 conference. Rotterdam: Cognitive Science Society.

Abstract

Studying physical rotation (i.e., rotation tasks during which figures can be physically rotated, such as through gestures) can offer insights also into problem solving processes at work during mental rotation. We present a novel method for behavioral pattern analysis which we applied to data from 2,999 physical rotation tasks gathered in-class from 50 secondary school students. The method uses normalized, resampled, time-dependent data on angular offsets between figures over time and agglomerative, correlation-based clustering. Each cluster represents a distinct behavioral pattern and its respective prototype a problem solving strategy. Results indicate that multiple strategies were employed: The dominant strategy matches the classical model of mental rotation, in which angular offsets between figures are decreased over time. For the secondary strategy, angular offsets were actually increased. A subsequent analysis shows that the secondary strategy was more frequently used for symmetric figures, possibly indicating problems with correctly matching segments across figures.
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Weiterführende Links
- Personenseiten
  
  Bertel, Sven
- Forschungsprojekt
  
  Kompetenzen für eine digitale Welt: partizipative Entwicklung von Apps zum Training räumlicher Fähigkeiten im Unterricht
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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An Interdisciplinary Perspective on AI-Supported Decision Making in Medicine

Ammeling, J. ., Aubreville, M. ., Fritz, A. ., Kießig, A. ., Krügel, S. ., & Uhl, M. . (2024). An Interdisciplinary Perspective on AI-Supported Decision Making in Medicine. Technology in Society, 102791.
- Suche auf Google Scholar
Exportformate
Weiterführende Links
- Personenseiten
  
  Aubreville, Marc
- Forschungsprojekt
  
  Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence
- Abteilung/Einrichtung
  
  FLAIR - Flensburg Artificial Intelligence Research
  
  CIVU – Center for Interaction, Visualization and Usability
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Data Science und Künstliche Intelligenz
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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Training for Ultrasound Imaging: An Evaluation of SonoGame

Gürgan, S. ., Henze, V. ., Gall, C. ., Schoenfisch, B. ., Brucker, S. ., Hahn, M. ., … Teistler, M. . (2024). Training for Ultrasound Imaging: An Evaluation of SonoGame. ACM Symposium on Spatial User Interaction (SUI 2024). Trier, Germany: ACM, New York. http://doi.org/10.1145/3677386.3688880
- Suche auf Google Scholar
- DOI Verweis
Exportformate
Weiterführende Links
- Personenseiten
  
  Bertel, Sven
  
  Teistler, Michael
- Abteilung/Einrichtung
  
  CIVU – Center for Interaction, Visualization and Usability
- Profilbereich
  
  Informatik und Gestaltung
- Forschungsfeld
  
  Human-Computer-Interaction
- Fachbereich
  
  Fachbereich 3: Information und Kommunikation
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