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pro vyhledávání: '"Nett A"'
Autor:
Lavanchy, Joel L., Ramesh, Sanat, Dall'Alba, Diego, Gonzalez, Cristians, Fiorini, Paolo, Muller-Stich, Beat, Nett, Philipp C., Marescaux, Jacques, Mutter, Didier, Padoy, Nicolas
Most studies on surgical activity recognition utilizing Artificial intelligence (AI) have focused mainly on recognizing one type of activity from small and mono-centric surgical video datasets. It remains speculative whether those models would genera
Externí odkaz:
http://arxiv.org/abs/2312.11250
Autor:
Nicole Foley, Florence Fouque, Qingxia Zhong, Herve Bossin, Jeremy Bouyer, Raman Velayudhan, Randall Nett, Anna Drexler
Publikováno v:
Infectious Diseases of Poverty, Vol 13, Iss 1, Pp 1-9 (2024)
Abstract Background Vector-borne diseases cause morbidity and mortality globally. However, some areas are more impacted than others, especially with climate change. Controlling vectors remains the primary means to prevent these diseases, but new, mor
Externí odkaz:
https://doaj.org/article/e4dbf27734f246d985e38192ffe39ebb
Autor:
Rahman, Obaidullah, Sauer, Ken D., Nagare, Madhuri, Bouman, Charles A., Melnyk, Roman, Tang, Jie, Nett, Brian
Deep learning (DL) shows promise of advantages over conventional signal processing techniques in a variety of imaging applications. The networks' being trained from examples of data rather than explicitly designed allows them to learn signal and nois
Externí odkaz:
http://arxiv.org/abs/2309.14367
Low x-ray dose is desirable in x-ray computed tomographic (CT) imaging due to health concerns. But low dose comes with a cost of low signal artifacts such as streaks and low frequency bias in the reconstruction. As a result, low signal correction is
Externí odkaz:
http://arxiv.org/abs/2309.13406
Autor:
Rahman, Obaidullah, Nagare, Madhuri, Sauer, Ken D., Bouman, Charles A., Melnyk, Roman, Nett, Brian, Tang, Jie
In computed tomographic imaging, model based iterative reconstruction methods have generally shown better image quality than the more traditional, faster filtered backprojection technique. The cost we have to pay is that MBIR is computationally expen
Externí odkaz:
http://arxiv.org/abs/2309.13399
Publikováno v:
Medical Education Online, Vol 29, Iss 1 (2024)
Introduction The initial year of medical school is linked to a decline in mental health. To assess mental health comprehensively, the dual-factor model posits the consideration of both psychopathology (e.g., depression) and positive mental health (e.
Externí odkaz:
https://doaj.org/article/77de72d29e684cbd81cdd7a65ce8ceee
Autor:
Polujanski, Sabine1 (AUTHOR) sabine.polujanski@med.uni-augsburg.de, Nett, Ulrike2 (AUTHOR), Rotthoff, Thomas1 (AUTHOR), Oezsoy, Melissa1,3 (AUTHOR), Schindler, Ann-Kathrin1 (AUTHOR)
Publikováno v:
Medical Education Online. 2024, Vol. 29 Issue 1, p1-11. 11p.
Publikováno v:
In Body Image December 2024 51
Publikováno v:
In Learning and Instruction February 2025 95
Autor:
CDF Collaboration, Aaltonen, T., Amerio, S., Amidei, D., Anastassov, A., Annovi, A., Antos, J., Apollinari, G., Appel, J. A., Arisawa, T., Artikov, A., Asaadi, J., Ashmanskas, W., Auerbach, B., Aurisano, A., Azfar, F., Badgett, W., Bae, T., Barbaro-Galtieri, A., Barnes, V. E., Barnett, B. A., Barria, P., Bartos, P., Bauce, M., Bedeschi, F., Behari, S., Bellettini, G., Bellinger, J., Benjamin, D., Beretvas, A., Bhatti, A., Bland, K. R., Blumenfeld, B., Bocci, A., Bodek, A., Bortoletto, D., Boudreau, J., Boveia, A., Brigliadori, L., Bromberg, C., Brucken, E., Budagov, J., Budd, H. S., Burkett, K., Busetto, G., Bussey, P., Butti, P., Buzatu, A., Calamba, A., Camarda, S., Campanelli, M., Canelli, F., Carls, B., Carlsmith, D., Carosi, R., Carrillo, S., Casal, B., Casarsa, M., Castro, A., Catastini, P., Cauz, D., Cavaliere, V., Cerri, A., Cerrito, L., Chen, Y. C., Chertok, M., Chiarelli, G., Chlachidze, G., Cho, K., Chokheli, D., Clark, A., Clarke, C., Convery, M. E., Conway, J., Corbo, M., Cordelli, M., Cox, C. A., Cox, D. J., Cremonesi, M., Cruz, D., Cuevas, J., Culbertson, R., d'Ascenzo, N., Datta, M., de Barbaro, P., Demortier, L., Deninno, M., D'Errico, M., Devoto, F., Di Canto, A., Di Ruzza, B., Dittmann, J. R., Donati, S., D'Onofrio, M., Dorigo, M., Driutti, A., Ebina, K., Edgar, R., Elagin, A., Erbacher, R., Errede, S., Esham, B., Farrington, S., Ramos, J. P. Fernández, Field, R., Flanagan, G., Forrest, R., Franklin, M., Freeman, J. C., Frisch, H., Funakoshi, Y., Galloni, C., Garfinkel, A. F., Garosi, P., Gerberich, H., Gerchtein, E., Giagu, S., Giakoumopoulou, V., Gibson, K., Ginsburg, C. M., Giokaris, N., Giromini, P., Glagolev, V., Glenzinski, D., Gold, M., Goldin, D., Golossanov, A., Gomez, G., Gomez-Ceballos, G., Goncharov, M., López, O. González, Gorelov, I., Goshaw, A. T., Goulianos, K., Gramellini, E., Grosso-Pilcher, C., da Costa, J. Guimaraes, Hahn, S. R., Han, J. Y., Happacher, F., Hara, K., Hare, M., Harr, R. F., Harrington-Taber, T., Hatakeyama, K., Hays, C., Heinrich, J., Herndon, M., Hocker, A., Hong, Z., Hopkins, W., Hou, S., Hughes, R. E., Husemann, U., Hussein, M., Huston, J., Introzzi, G., Iori, M., Ivanov, A., James, E., Jang, D., Jayatilaka, B., Jeon, E. J., Jindariani, S., Jones, M., Joo, K. K., Jun, S. Y., Junk, T. R., Kambeitz, M., Kamon, T., Karchin, P. E., Kasmi, A., Kato, Y., Ketchum, W., Keung, J., Kilminster, B., Kim, D. H., Kim, H. S., Kim, J. E., Kim, M. J., Kim, S. H., Kim, S. B., Kim, Y. J., Kim, Y. K., Kimura, N., Kirby, M., Kondo, K., Kong, D. J., Konigsberg, J., Kotwal, A. V., Kreps, M., Kroll, J., Kruse, M., Kuhr, T., Kurata, M., Laasanen, A. T., Lammel, S., Lancaster, M., Lannon, K., Latino, G., Lee, H. S., Lee, J. S., Leo, S., Leone, S., Lewis, J. D., Limosani, A., Lipeles, E., Lister, A., Liu, Q., Liu, T., Lockwitz, S., Loginov, A., Lucchesi, D., Lucà, A., Lueck, J., Lujan, P., Lukens, P., Lungu, G., Lys, J., Lysak, R., Madrak, R., Maestro, P., Malik, S., Manca, G., Manousakis-Katsikakis, A., Marchese, L., Margaroli, F., Marino, P., Matera, K., Mattson, M. E., Mazzacane, A., Mazzanti, P., McNulty, R., Mehta, A., Mehtala, P., Mesropian, C., Miao, T., Michielin, E., Mietlicki, D., Mitra, A., Miyake, H., Moed, S., Moggi, N., Moon, C. S., Moore, R., Morello, M. J., Mukherjee, A., Muller, Th., Murat, P., Mussini, M., Nachtman, J., Nagai, Y., Naganoma, J., Nakano, I., Napier, A., Nett, J., Nigmanov, T., Nodulman, L., Noh, S. Y., Norniella, O., Oakes, L., Oh, S. H., Oh, Y. D., Okusawa, T., Orava, R., Ortolan, L., Pagliarone, C., Palencia, E., Palni, P., Papadimitriou, V., Parker, W., Pauletta, G., Paulini, M., Paus, C., Phillips, T. J., Piacentino, G., Pianori, E., Pilot, J., Pitts, K., Plager, C., Pondrom, L., Poprocki, S., Potamianos, K., Pranko, A., Prokoshin, F., Ptohos, F., Punzi, G., Fernández, I. Redondo, Renton, P., Rescigno, M., Rimondi, F., Ristori, L., Robson, A., Rodriguez, T., Rolli, S., Ronzani, M., Roser, R., Rosner, J. L., Ruffini, F., Ruiz, A., Russ, J., Rusu, V., Sakumoto, W. K., Sakurai, Y., Santi, L., Sato, K., Saveliev, V., Savoy-Navarro, A., Schlabach, P., Schmidt, E. E., Schwarz, T., Scodellaro, L., Scuri, F., Seidel, S., Seiya, Y., Semenov, A., Seo, H., Sforza, F., Shalhout, S. Z., Shears, T., Shepard, P. F., Shimojima, M., Shochet, M., Shreyber-Tecker, I., Simonenko, A., Sliwa, K., Smith, J. R., Snider, F. D., Song, H., Sorin, V., Denis, R. St., Stancari, M., Stentz, D., Strologas, J., Sudo, Y., Sukhanov, A., Suslov, I., Takemasa, K., Takeuchi, Y., Tang, J., Tecchio, M., Teng, P. K., Thom, J., Thomson, E., Thukral, V., Toback, D., Tokar, S., Tollefson, K., Tomura, T., Tonelli, D., Torre, S., Torretta, D., Totaro, P., Trovato, M., Ukegawa, F., Uozumi, S., Vázquez, F., Velev, G., Vellidis, C., Vernieri, C., Vidal, M., Vilar, R., Vizán, J., Vogel, M., Volpi, G., Wagner, P., Wallny, R., Wang, S. M., Waters, D., Wester III, W. C., Whiteson, D., Wicklund, A. B., Wilbur, S., Williams, H. H., Wilson, J. S., Wilson, P., Winer, B. L., Wittich, P., Wolbers, S., Wolfmeister, H., Wright, T., Wu, X., Wu, Z., Yamamoto, K., Yamato, D., Yang, T., Yang, U. K., Yang, Y. C., Yao, W. -M., Yeh, G. P., Yi, K., Yoh, J., Yorita, K., Yoshida, T., Yu, G. B., Yu, I., Zanetti, A. M., Zeng, Y., Zhou, C., Zucchelli, S.
A study of initial-state gluon radiation (ISR) in hadron collisions is presented using Drell-Yan (DY) events produced in proton-antiproton collisions by the Tevatron collider at a center-of-mass energy of 1.96 TeV. This paper adopts a novel approach
Externí odkaz:
http://arxiv.org/abs/2110.14878