Zobrazeno 1 - 10
of 1 074
pro vyhledávání: '"Calivà, A."'
Autor:
Caliva, Victor, Fuks, Johanna I
The transition into a strongly-correlated regime of 3 fermions trapped in a one-dimensional harmonic potential is investigated. This interesting, but little-studied system, allows us to identify characteristic features of the regime, some of which ar
Externí odkaz:
http://arxiv.org/abs/2401.04733
Self-supervised speech representation learning (S3RL) is revolutionizing the way we leverage the ever-growing availability of data. While S3RL related studies typically use large models, we employ light-weight networks to comply with tight memory of
Externí odkaz:
http://arxiv.org/abs/2303.04255
Autor:
Macha, Sashank, Oza, Om, Escott, Alex, Caliva, Francesco, Armitano, Robbie, Cheekatmalla, Santosh Kumar, Parthasarathi, Sree Hari Krishnan, Liu, Yuzong
Publikováno v:
ICASSP 2023
Fixed-point (FXP) inference has proven suitable for embedded devices with limited computational resources, and yet model training is continually performed in floating-point (FLP). FXP training has not been fully explored and the non-trivial conversio
Externí odkaz:
http://arxiv.org/abs/2303.02284
Autor:
Cossio, F., Achari, B.R., Agrawal, N., Alexeev, M., Alice, C., Antonioli, P., Baldanza, C., Barion, L., Bortone, A., Calivà, A., Capua, M., Chiosso, M., Contalbrigo, M., Da Rocha Rolo, M., De Caro, A., De Gruttola, D., Dellacasa, G., Falchieri, D., Fazio, S., Funicello, N., Garbini, M., Giacalone, M., Giordano, D., Mignone, M., Malaguti, R., Preghenella, R., Panzieri, D., Paladino, A., Occhiuto, L., Rignanese, L.P., Ripoli, C., Rubini, N., Ruspa, M., Tassi, E., Tuvé, C., Vallarino, S., Wheadon, R.
Publikováno v:
In Nuclear Inst. and Methods in Physics Research, A December 2024 1069
Autor:
Alice, Chiara, Achari, B.R., Agrawal, N., Alexeev, M., Antonioli, P., Baldanza, C., Barion, L., Calivà, A., Capua, M., Chiosso, M., Contalbrigo, M., Cossio, F., Da Rocha Rolo, M., De Caro, A., De Gruttola, D., Dellacasa, G., Falchieri, D., Fazio, S., Funicello, N., Garbini, M., Giacalone, M., Giordano, D., Mignone, M., Malaguti, R., Preghenella, R., Panzieri, D., Paladino, A., Occhiuto, L., Rignanese, L.P., Ripoli, C., Ruspa, M., Rubini, N., Tassi, E., Tuvé, C., Vallarino, S., Wheadon, R.
Publikováno v:
In Nuclear Inst. and Methods in Physics Research, A November 2024 1068
Publikováno v:
In Poultry Science June 2024 103(6)
Deep Learning (DL) has shown potential in accelerating Magnetic Resonance Image acquisition and reconstruction. Nevertheless, there is a dearth of tailored methods to guarantee that the reconstruction of small features is achieved with high fidelity.
Externí odkaz:
http://arxiv.org/abs/2011.00070
Autor:
Desai, Arjun D., Caliva, Francesco, Iriondo, Claudia, Khosravan, Naji, Mortazi, Aliasghar, Jambawalikar, Sachin, Torigian, Drew, Ellermann, Jutta, Akcakaya, Mehmet, Bagci, Ulas, Tibrewala, Radhika, Flament, Io, O`Brien, Matthew, Majumdar, Sharmila, Perslev, Mathias, Pai, Akshay, Igel, Christian, Dam, Erik B., Gaj, Sibaji, Yang, Mingrui, Nakamura, Kunio, Li, Xiaojuan, Deniz, Cem M., Juras, Vladimir, Regatte, Ravinder, Gold, Garry E., Hargreaves, Brian A., Pedoia, Valentina, Chaudhari, Akshay S.
Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI
Externí odkaz:
http://arxiv.org/abs/2004.14003
Autor:
Namiri, Nikan K., Flament, Io, Astuto, Bruno, Shah, Rutwik, Tibrewala, Radhika, Caliva, Francesco, Link, Thomas M., Pedoia, Valentina, Majumdar, Sharmila
Purpose: To evaluate the diagnostic utility of two convolutional neural networks (CNNs) for severity staging of anterior cruciate ligament (ACL) injuries. Materials and Methods: This retrospective analysis was conducted on 1243 knee MR images (1008 i
Externí odkaz:
http://arxiv.org/abs/2003.09089
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