Elenco Pubblicazioni - Publications (1545)
Federico Giulio, Carrara Fabio, Amato Giuseppe and Di Benedetto Marco: "Spatio-Temporal 3D Reconstruction from Frame Sequences and Feature Points"
Written by GIULIO FEDERICO
Reconstructing a large real environment is a fundamental task to promote eXtended Reality adoption in industrial and entertainment fields. However, the short range of depth cameras, the sparsity of LiDAR sensors, and the huge computational…
Colantonio, S., Berti, A., Buongiorno, R., Del Corso, G., Pachetti, E., Pascali, M. A., ... & Tsiknakis, M. (2023, December). AI trustworthiness in prostate cancer imaging: a look at algorithmic and system transparency. In 2023 IEEE EMBS Special Topi
Written by EVA PACHETTI
A responsible approach to artificial intelligence and machine learning technologies, grounded in sound scientific foundations, technical robustness, rigorous testing and validation, risk-based continuous monitoring and alignment with human values is imperative to guarantee their favorable…
Pachetti, E., & Colantonio, S. (2024). Hallucinating for Diagnosing: One-Shot Medical Image Classification Leveraging Score-Based Generative Models. In Medical Imaging with Deep Learning.
Written by EVA PACHETTI
Deep learning models in data-scarce domains, such as medical imaging, often suffer from poor performance due to the challenges of acquiring large amounts of labeled data. Few-shot learning offers a promising solution to this problem.…
Pachetti, E. & Colantonio, S. (2024). Seeing More with Less: Meta-Learning and Diffusion Models for Tumor Characterization in Low-data Settings
Written by EVA PACHETTI
While deep learning excels in many areas, its application in medicine is hindered by limited data, which restricts model generalizability. Few-shot learning has emerged as a potential solution to this problem. In this work, we…
Pachetti, E., Tsaftaris, S. A., & Colantonio, S. (2024). Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification. arXiv preprint arXiv:2403.17530.
Written by EVA PACHETTI
Background and objective: Employing deep learning models in critical domains such as medical imaging poses challenges associated with the limited availability of training data. We present a strategy for improving the performance and generalization capabilities…
News
- Prof. Mario Innocenti, Dipartimento di Ingegneria dell’Informazione (retired), Università di Pisa, "Analysis and Control of Dynamical Systems: a State Space Approach", 10-13 June 2025
- Assistant Professor Xiaomeng Li, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, "Deep Learning for Medical Image Analysis", 21-23, 28 July 2025
- Modifica Lezione - Dr. Adrian Wallwork, "Academic English: Writing and Presenting WITH the support of LLMs", 6,7,11,13,18,20,25,27 March 2025
- Prof. Sajal K. Das, Missouri University of Science and Technology Rolla, MO, USA, "Secure and Resilient Cyber-Physical Systems for Smart Living", 12-15 May 2025
- MODIFICA DATE CORSO - Prof. Nicola Tonellotto, University of Pisa – Italy, PhD. Guglielmo Faggioli, Università degli Studi di Padova - Italy, "Privacy Preserving Information Access", 19-23 May 2025
