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Integration of numeric and symbolic information for semantic image interpretation.

, and . Intelligenza Artificiale, 10 (1): 33-47 (2016)

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Integration of numeric and symbolic information for semantic image interpretation., and . Intelligenza Artificiale, 10 (1): 33-47 (2016)EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case., , , , , , , , , and . CoRR, (2021)Explainable AI meets persuasiveness: Translating reasoning results into behavioral change advice., , and . Artif. Intell. Medicine, (2020)An End-to-End Semantic Platform for Nutritional Diseases Management., and . ISWC (2), volume 11779 of Lecture Notes in Computer Science, page 363-381. Springer, (2019)Declarative Process Mining for Software Processes: The RuM Toolkit and the Declare4Py Python Library., , , and . PROFES (2), volume 14484 of Lecture Notes in Computer Science, page 13-19. Springer, (2023)Ontology Based Semantic Image Interpretation.. DC@AI*IA, volume 1485 of CEUR Workshop Proceedings, page 19-24. CEUR-WS.org, (2015)SeXAI: Introducing Concepts into Black Boxes for Explainable Artificial Intelligence., and . XAI.it@AI*IA, volume 2742 of CEUR Workshop Proceedings, page 41-54. CEUR-WS.org, (2020)Machine Learning for Utility Prediction in Argument-Based Computational Persuasion., , , and . CoRR, (2021)Persuasive Explanation of Reasoning Inferences on Dietary Data., , and . PROFILES/SEMEX@ISWC, volume 2465 of CEUR Workshop Proceedings, page 46-61. CEUR-WS.org, (2019)Explanations in Digital Health: The Case of Supporting People Lifestyles., , and . AIME, volume 12721 of Lecture Notes in Computer Science, page 287-292. Springer, (2021)