Projects
Contact person, projects
- SHEREC: Safe, Healthy and Environmental Ship Recycling (2024 - 2027)
- Transformer models for point cloud analysis (2022)
- 6-DoF localization uncertainty for autonomous underwater vehicles (2018 - 2021)
- Underwater 6D Pose Estimation (2018 - 2021)
- Self-supervised learning when you don’t have enough labeled data (2015 - 2023)
Expertise
Contact person, expertise
Publications
- 3D Pointcloud Registration In-the-wild
- CAPTIV8: A Comprehensive Large Scale Capsule Endoscopy Dataset For Integrated Diagnosis
- SAFESUB: Safe and Autonomous Subsea Intervention
- Sensor‑guided motions for manipulators in manufacturing Read publication
- This Changes to That : Combining Causal and Non-Causal Explanations to Generate Disease Progression in Capsule Endoscopy
- Multi-label Video Classification for Underwater Ship Inspection
- Concept-based reasoning in medical imaging
- Evaluating clinical diversity and plausibility of synthetic capsule endoscopic images Read publication
- From labels to priors in capsule endoscopy: a prior guided approach for improving generalization with few labels Read publication
- Autonomous subsea intervention (SEAVENTION) Read publication
Other
- Robotics and drones for inspection and maintenance of offshore and onshore energy infrastructure
- Introduction to ADRF2024 workshop on Generative AI in inspection and maintenance (I&M): Learnings across sectors, low-hanging industry use cases, and future challenges and opportunities
- Enhancing Safety in Airport Ground Operations through Human-AI Teaming, Insights from the FLAIT Project
- SAFESUB: Safe and Autonomous Subsea Intervention
- Inspection and maintenance robotics: Status and trends
- Robotics and drones for inspection and maintenance of offshore and onshore energy infrastructure
- Language models and human-AI teaming for safety and quality in ground operations on airports – experiences from the FLAIT project
- Multi-label Video Classification for Underwater Ship Inspection
- Kunstig intelligens skal gjøre flyplassens farligste område tryggere: – Vil fjerne de mest vanlige årsakene til uhellene
- Semantically consistent self-supervised representation learning on point clouds