Zobrazeno 1 - 10
of 569
pro vyhledávání: '"Cirrone, P"'
Autor:
Singh, Pranav, Cirrone, Jacopo
Recent advancements in self-supervised learning have unlocked the potential to harness unlabeled data for auxiliary tasks, facilitating the learning of beneficial priors. This has been particularly advantageous in fields like medical image analysis,
Externí odkaz:
http://arxiv.org/abs/2402.02367
Autor:
Narayanan, Abhishek, Musthyala, Rushabh, Sankar, Rahul, Nistala, Anirudh Prasad, Singh, Pranav, Cirrone, Jacopo
Visual Question Answering (VQA) in the medical domain presents a unique, interdisciplinary challenge, combining fields such as Computer Vision, Natural Language Processing, and Knowledge Representation. Despite its importance, research in medical VQA
Externí odkaz:
http://arxiv.org/abs/2401.13081
Autor:
Rodrigues, M. R. D., Bonasera, A., Scisciò, M., Pérez-Hernández, J. A., Ehret, M., Filippi, F., Andreoli, P. L., Huault, M., Larreur, H., Singappuli, D., Molloy, D., Raffestin, D., Alonzo, M., Rapisarda, G. G., Lattuada, D., Guardo, G. L., Verona, C., Consoli, Fe., Petringa, G., McNamee, A., La Cognata, M., Palmerini, S., Carriere, T., Cipriani, M., Di Giorgio, G., Cristofari, G., De Angelis, R., Cirrone, G. A. P., Margarone, D., Giuffrida, L., Batani, D., Nicolai, P., Batani, K., Lera, R., Volpe, L., Giulietti, D., Agarwal, S., Krupka, M., Singh, S., Consoli, Fa.
Laser technologies improved after the understanding of the Chirped Pulse Amplification (CPA) which allows energetic laser beams to be compressed to tens of femtosecond (fs) pulse durations and focused to few $\mu$m. Protons of tens of MeV can be acce
Externí odkaz:
http://arxiv.org/abs/2312.09145
Autor:
Singh, Pranav, Chukkapalli, Raviteja, Chaudhari, Shravan, Chen, Luoyao, Chen, Mei, Pan, Jinqian, Smuda, Craig, Cirrone, Jacopo
Publikováno v:
Singh, P., Chukkapalli, R., Chaudhari, S. et al. Shifting to machine supervision: annotation-efficient semi and self-supervised learning for automatic medical image segmentation and classification. Sci Rep 14, 10820 (2024)
Advancements in clinical treatment are increasingly constrained by the limitations of supervised learning techniques, which depend heavily on large volumes of annotated data. The annotation process is not only costly but also demands substantial time
Externí odkaz:
http://arxiv.org/abs/2311.10319
Autor:
Menichelli, M., Antognini, L., Aziz, S., Bashiri, A., Bizzarri, M., Calcagnile, L., Caprai, M., Caputo, D., Caricato, A. P., Catalano, R., Chilà, D., Cirrone, G. A. P., Croci, T., Cuttone, G., De Cesare, G., Dunand, S., Fabi, M., Frontini, L., Grimani, C., Ionica, M., Kanxheri, K., Large, M., Liberali, V., Lovecchio, N., Martino, M., Maruccio, G., Mazza, G., Monteduro, A. G., Morozzi, A., Moscatelli, F., Nascetti, A., Pallotta, S., Papi, A., Passeri, D., Pedio, M., Petasecca, M., Petringa, G., Peverini, F., Piccolo, L., Placidi, P., Quarta, G., Rizzato, S., Rossi, G., Sabbatini, F., Servoli, L., Stabile, A., Talamonti, C., Thomet, J. E., Tosti, L., Villani, M., Wheadon, R. J., Wyrsch, N., Zema, N.
Hydrogenated amorphous silicon (a-Si:H) is a material having an intrinsically high radiation hardness that can be deposited on flexible substrates like Polyimide. For these properties a-Si:H can be used for the production of flexible sensors. a-Si:H
Externí odkaz:
http://arxiv.org/abs/2310.00495
Autor:
Singh, Pranav, Chen, Luoyao, Chen, Mei, Pan, Jinqian, Chukkapalli, Raviteja, Chaudhari, Shravan, Cirrone, Jacopo
The task of medical image segmentation presents unique challenges, necessitating both localized and holistic semantic understanding to accurately delineate areas of interest, such as critical tissues or aberrant features. This complexity is heightene
Externí odkaz:
http://arxiv.org/abs/2308.10488
Autor:
Singh, Pranav, Cirrone, Jacopo
In healthcare and biomedical applications, extreme computational requirements pose a significant barrier to adopting representation learning. Representation learning can enhance the performance of deep learning architectures by learning useful priors
Externí odkaz:
http://arxiv.org/abs/2308.10064
Autor:
Sytov, Alexei, Bandiera, Laura, Cho, Kihyeon, Hwang, Soonwook, Cirrone, Giuseppe Antonio Pablo, Pandola, Luciano, Guatelli, Susanna, Rosenfeld, Anatoly, Haurylavets, Viktar, Tikhomirov, Victor, Ivanchenko, Vladimir
Electromagnetic processes of charged particles interaction with oriented crystals provide a wide variety of innovative applications such as beam steering, crystal-based extraction/collimation of leptons and hadrons in an accelerator, a fixed-target e
Externí odkaz:
http://arxiv.org/abs/2303.04385
Autor:
Grimani, Catia, Fabi, Michele, Sabbatini, Federico, Villani, Mattia, Calcagnile, Lucio, Caricato, Anna Paola, Catalano, Roberto, Cirrone, Giuseppe Antonio Pablo, Croci, Tommaso, Cuttone, Giacomo, Dunand, Sylvain, Frontini, Luca, Ionica, Maria, Kanxheri, Keida, Large, Matthew, Liberali, Valentino, Martino, Maurizio, Maruccio, Giuseppe, Mazza, Giovanni, Menichelli, Mauro, Monteduro, Anna Grazia, Morozzi, Arianna, Moscatelli, Francesco, Pallotta, Stefania, Passeri, Daniele, Pedio, Maddalena, Petasecca, Marco, Petringa, Giada, Peverini, Francesca, Piccolo, Lorenzo, Placidi, Pisana, Quarta, Gianluca, Rizzato, Silvia, Stabile, Alberto, Talamonti, Cinzia, Wheadon, Richard James, Wyrsch, Nicolas, Servoli, Leonello
The characteristics of a hydrogenated amorphous silicon (a-Si:H) detector are presented here for monitoring in space solar flares and the evolution of large energetic proton events up to hundreds of MeV. The a-Si:H presents an excellent radiation har
Externí odkaz:
http://arxiv.org/abs/2302.00339
Autor:
Pranav Singh, Raviteja Chukkapalli, Shravan Chaudhari, Luoyao Chen, Mei Chen, Jinqian Pan, Craig Smuda, Jacopo Cirrone
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Advancements in clinical treatment are increasingly constrained by the limitations of supervised learning techniques, which depend heavily on large volumes of annotated data. The annotation process is not only costly but also demands substan
Externí odkaz:
https://doaj.org/article/aab6c2c1aca247e8ab62a6ba1ddc8780