STENDHAL (“Spatio-Temporal Enhancement of Neural Nets for Deeply Hierarchical Automatised Logic”) will push the boundaries of spatial analysis by introducing spatio-temporal capabilities in sequences of images. This breakthrough will enable advanced analysis of videos and facilitate longitudinal studies in healthcare, empowering researchers and practitioners to extract valuable insights from visual data. In addition, the project will pioneer the integration of spatial model checking with neural networks. By combining the precision of neural networks with expert-driven monitoring of requirements, such as protocols, guidelines, and safety properties, we aim to achieve unprecedented levels of accuracy and efficiency in complex systems.
STENDHAL’s innovative methods will be rigorously validated through case studies in the healthcare and cyber-physical domains. These real-world applications will demonstrate the practical implications of our research, showcasing the great potential for enhancing decision-making, safety, and performance in critical domains.
STENDHAL is led by the University of Pisa, in collaboration with the National Research Council (CNR) and the University of Udine (where I am the Principal Investigator). The expertise and resources of multiple institutions will ensure a comprehensive exploration of the project’s objectives.
More details will be on the forthcoming project’s web page