ExpectedOutcome:
Project results are expected to contribute to some of the following expected outcomes:
improved acquisition, quality, interoperability and analysis of imaging data from different disciplines (e.g.: health & food, climate and environmental research, digital transformation);wider use of image analysis services based on AI in different scientific areas.
Scope:The availability of high-performance image analysis tools, including those based on AI, through the provision of RI services, has a great potential to improve the use of image data for research purposes. These services enable better use of imaging data by aligning data formats, ensuring better data quality and noise reduction, improving interoperability, applying advanced data analysis, interpretation and potentially visualisation, as well as by integrating imaging data with other data sets of different types.
Use of artificial intelligence as enabler for better exploitation of data sets for research queries will be an important contribution from research infrastructures to the Commission’s AI strategy proposed in the Commission’s White Paper On Artificial I...
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ExpectedOutcome:
Project results are expected to contribute to some of the following expected outcomes:
improved acquisition, quality, interoperability and analysis of imaging data from different disciplines (e.g.: health & food, climate and environmental research, digital transformation);wider use of image analysis services based on AI in different scientific areas.
Scope:The availability of high-performance image analysis tools, including those based on AI, through the provision of RI services, has a great potential to improve the use of image data for research purposes. These services enable better use of imaging data by aligning data formats, ensuring better data quality and noise reduction, improving interoperability, applying advanced data analysis, interpretation and potentially visualisation, as well as by integrating imaging data with other data sets of different types.
Use of artificial intelligence as enabler for better exploitation of data sets for research queries will be an important contribution from research infrastructures to the Commission’s AI strategy proposed in the Commission’s White Paper On Artificial Intelligence - A European approach to excellence and trust (COM(2020) 65 final). Proposals under this topic bring together several complementary and interdisciplinary RIs to provide trans-national access (in-person, when the user visits the infrastructure to make use of it or remote access) and/or virtual access to integrated and customised RI services for challenge-driven research and innovation. Access also includes ad hoc users’ training and scientific and technical support. Harmonisation, customisation and virtualisation of RI services will also be supported.
Successful proposals will offer services, including AI-based services for improved analysis of imaging data in different thematic areas (e.g. environmental monitoring, life sciences, chemistry, physics,...). Appropriate links and complementarities must be ensured with the existing AI4EU platform[1] and relevant activities under Pillar II of Horizon Europe.
AI-based tools and services will make use of the EOSC commons as working environment where these tools, services and relevant data sets will be made findable and accessible for use, thus making EOSC operational for the delivery of research infrastructure data services for thematic research challenges.
Cross-cutting Priorities:Co-programmed European PartnershipsEOSC and FAIR data
[1]https://www.ai4eu.eu/
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