Abstract: Semantic Image Interpretation (SII) is the task of extracting structured semantic descriptions from images. This task is suitable for Logic Tensor Networks (LTNs), a new Statistical Relational Learning framework which integrates neural networks with fuzzy logic. LTNs allows learning and reasoning with data and logical constraints. In this seminar, we show LTNs and its evaluation on the classification of image objects and part-of relations between them. The use of logical constraints improves the performance of purely data-driven approaches. Moreover, the logical constraints add robustness when the training labels are affected by errors.
Seminario proposto nell’ambito del Corso di Sistemi Intelligenti, L.M. Ingegneria Informatica