Shared daTabase for Optronic Image Recognition and Evaluation


The main challenges of STORE are to build a sustainable shared and scalable database addressing the evolution of threats and the diversity of terrestrial environments, and to develop and benchmark high-performance AI-based image recognition capabilities.

Research objectives

  • Increase readiness of future technologies for upscaling and secure data sharing
  • Define, measure, and increase performances of AI algorithms on defence image recognition use-cases beyond state-of-the-art

Technical objectives

  • Set-up new frameworks for data production and sharing, ensuring adaptability and compliance with interoperability standards
  • Set-up new frameworks for efficient recognition software co-development through the development of a leading edge AI factory for defence functionalities benchmark with a research reproducibility guarantee

Users oriented objectives

  • Achieve a representative and reliable image database versus targeted use cases
  • Define and set-up appropriate governance model for data sharing within the project and beyond
  • Integrate software systems recognition functions and evaluate performances through a final demonstration
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