Shared daTabase for Optronics image Recognition and Evaluation

Why STORE?
Faced with the emergence of new threats and their constant evolution (hypersonic missiles, combat drones, swarms of drones, …), Forces have an increasing need for AI-based image recognition systems to fasten decision-making, enhance situation awareness, responsiveness, and survivability. The complexity of the development of such systems is linked to the lack of representative defence images, associated tools and infrastructure to share them properly between the countries. To ensure autonomy and sovereignty, the European industry needs to work collectively to build a database populated with military threats, which will allow for developing, training, and testing AI based image recognition systems.
What is STORE?
STORE (Shared daTabase for Optronic Image Recognition and Evaluation) project lays the foundations for Europe’s first shared, scalable database of defence imagery and explores different threat detection algorithm solutions. In particular, it will address issues of data governance and the cost-effective development of sovereign technologies.
STORE achievements will help setting-up future functionalities related to increased situational awareness for the European forces and supporting Man Unmanned Teaming (MUM-T) operations where Automatic Target Detection and Recognition (ATD/R), tracking and semantic understanding in complex situations are required. STORE will offer short and medium-term keys to detect and recognize new threats and to counter their evolution. Three use cases built around various threat types are addressed by STORE :
• Battle tanks & Infantry Vehicles
• Drone & Drones swarm
• Hypersonic threats




STORE will develop a new type of distributed database architecture based on a set of local database nodes with dedicated synchronization and coordination services, secured by most advanced technologies.
The resulting architecture will enable shared governance among member states by enabling application of exchange restriction rules founded on policy and releasability. Besides, the architecture will allow for strongly decoupling data acquisition, cleaning and consolidation processes from database exploitation for scientific or engineering purposes.


Leading edge AI factory dedicated to image recognition for detection
STORE will enable to extend the operational use of image recognition systems by making the systems more robust to the variety of observation conditions and by addressing new forms of threats such as small drones and drone swarms, loitering munitions and hypersonic threats. Additionally, STORE potential to mature AI methods will allow an effective way to assess potential novel threats arising with the support of AI based systems.
STORE will address newest technologies for the sharing of data and models across borders, companies and institutions from the defence domain in  a controlled and trustworthy manner while maintaining privacy and security.
A software architecture framework will mature decentralized learning techniques to decouple model training from a central database and therefore allowing to train AI models without exposing critical data.

Future technologies for decentralized learning techniques exploiting shared database
STORE will address newest technologies for the sharing of data and models across borders, companies and institutions from the defence domain in  a controlled and trustworthy manner while maintaining privacy and security.
A software architecture framework will mature decentralized learning techniques to decouple model training from a central database and therefore allowing to train AI models without exposing critical data.


Evaluation of AI recognition systems integrated on demonstrators
STORE will ensure an objective evaluation of performances of AI recognition methods through a common annotation platform of acquired images, the use of shared metrics and benchmark tools in order to measure the performance of partners algorithms on the addressed use cases. The benchmark will be independent, as conducted by a dedicated team.
The evaluation will be carried out on integrated demonstrators comprised of optronics sensors used for data collection. AI technologies selected through the benchmark activities will be integrated in customized hardware near sensors and will be tested during field demonstrations implementing the STORE use cases at the end of the project.