Sensonic is a pioneer and trailblazer for the use of fiber optic sensing in the global railway market.
In the project with Frauscher Sensonic, the research focuses on meta-learning, few-shot learning, domain changes, representation fusion and outlier detection as well as transductive learning and associative memory. The latest findings and models of Modern Hopfield Networks will be used and an attempt will be made to apply Transductive Deep Learning for small data sets.