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Displaying items by tag: Deep Learning
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Bertelli E, Mercatelli L, Marzi C, Pachetti E, Baccini M, Barucci A, Colantonio S, Gherardini L, Lattavo L, Pascali MA, Agostini S, Miele V. Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI
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Carloni G. & Berti A., et al. "On the Applicability of Prototypical Part Learning in Medical Images: Breast Masses Classification Using ProtoPNet" in ICPR 2022 International Conference on Pattern Recognition - AIHA 2nd International Workshop, 2022
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Carloni, G., & Colantonio, S. (2024). Exploiting Causality Signals in Medical Images: A Pilot Study with Empirical Results. arXiv preprint arXiv:2309.10399.
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Carloni, G., Berti, A., & Colantonio, S. (2024). The role of causality in explainable artificial intelligence. arXiv preprint arXiv:2309.09901.
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Carloni, G., Berti, A., Iacconi, C., Pascali, M. A., & Colantonio, S. (2022, August). On the Applicability of Prototypical Part Learning in Medical Images: Breast Masses Classification Using ProtoPNet. In Int Conf on Pattern Recognition
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D. A. Coccomini, N. Messina, C. Gennaro, and F. Falchi. 2022. Combining EfficientNet and Vision Transformers for Video Deepfake Detection. In Image Analysis and Processing – ICIAP 2022: 21st International Conference, Lecce, Italy, May 23–27, 2022
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D. A. Coccomini, R. Caldelli, F. Falchi, C. Gennaro, and G. Amato. 2022. Cross-Forgery Analysis of Vision Transformers and CNNs for Deepfake Image Detection. In Proceedings of International Workshop on Multimedia AI against Disinformation, NY, USA
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Giacomo Giorgi, Antonio La Marra, Fabio Martinelli, Paolo Mori, and Andrea Saracino : Smart Parental Advisory: A Usage Control and Deep Learning-Based Framework for Dynamic Parental Control on Smart TV
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Giacomo Giorgi, Fabio Martinelli, Andrea Saracino, Mina Sheikhalishahi : Try Walking in My Shoes, if you can: Accurate Gait Recognition through Deep Learning
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Giacomo Giorgi, Fabio Martinelli, Andrea Saracino, Mina Sheikhalishahi : Walking Through the Deep: Gait Analysis for User Authentication through Deep Learning
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