Artificial Intelligence (AI) has become indispensable for analyzing large-scale datasets, particularly in the realm of 3D image volumes. However, effectively harnessing AI for such tasks often requires advanced algorithms and high-performance computing (HPC) resources, presenting significant challenges for non-technical users. To overcome these barriers, we present KI-Morph, a novel software platform for large-scale image analysis seamlessly integrated with the bwHPC infrastructure. It offers a user-friendly interface, enabling sophisticated AI-driven analysis without requiring technical expertise in either AI or HPC. KI-Morph prioritizes data privacy and sovereignty, ensuring that users retain full control over their data. Additionally, the components developed for the platform support researchers also with science outreach by enabling the creation of interactive online visualizations, for example using the 2D, 3D and augmented reality viewers.
SEEK ID: https://publications.h-its.org/publications/2000
Filename: Zeilmann_-_KI-Morph_–_User-friendly_large-scale_image_analysis_&_AI_on_bwHPC_systems_-_Preprint.pdf
Format: PDF document
Size: 810 KB
SEEK ID: https://publications.h-its.org/publications/2000
Research Groups: Data Mining and Uncertainty Quantification
Publication type: InProceedings
Publisher: 10th bwHPC Symposium
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Created: 30th Jan 2025 at 15:26
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