Zobrazeno 1 - 10
of 156 221
pro vyhledávání: '"Maier A. A."'
Autor:
Boggiano, Hilario D., Roqueiro, Nicolas A., Zhang, Haizhong, Krivitsky, Leonid, Cortes, Emiliano, Maier, Stefan A., Bragas, Andrea V., Kuznetsov, Arseniy, Grinblat, Gustavo
Nanostructured high-index dielectrics have shown great promise as low-loss photonic platforms for wavefront control and enhancing optical nonlinearities. However, their potential as optomechanical resonators has remained unexplored. In this work, we
Externí odkaz:
http://arxiv.org/abs/2410.02431
Autor:
Xie, Zhaoyang, Li, Chi, Murali, Krishna, Yu, Haoyi, Liu, Changxu, Lu, Yiqing, Maier, Stefan A., Bhaskaran, Madhu, Ren, Haoran
Phase-change materials (PCMs) are increasingly recognised as promising platforms for tunable photonic devices due to their ability to modulate optical properties through solid-state phase transitions. Ultrathin and low-loss PCMs are highly valued for
Externí odkaz:
http://arxiv.org/abs/2410.02413
Autor:
Aalbers, J., Abe, K., Adrover, M., Maouloud, S. Ahmed, Althueser, L., Amaral, D. W. P., Andrieu, B., Angelino, E., Martin, D. Antón, Antunovic, B., Aprile, E., Babicz, M., Bajpai, D., Balzer, M., Barberio, E., Baudis, L., Bazyk, M., Bell, N. F., Bellagamba, L., Biondi, R., Biondi, Y., Bismark, A., Boehm, C., Boese, K., Braun, R., Breskin, A., Brommer, S., Brown, A., Bruni, G., Budnik, R., Cai, C., Capelli, C., Chauvin, A., Chavez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Doerenkamp, M., Drexlin, G., Eitel, K., Elykov, A., Engel, R., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fujikawa, K., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Garroum, N., Giacomobono, R., Girard, F., Glade-Beucke, R., Glück, F., Grandi, L., Grigat, J., Größle, R., Guan, H., Guida, M., Gyorgy, P., Hammann, R., Hannen, V., Hansmann-Menzemer, S., Hargittai, N., Higuera, A., Hils, C., Hiraoka, K., Hoetzsch, L., Hoferichter, M., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., James, R. S., Joerg, F., Kahlert, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Keller, M., Kharbanda, P., Kilminster, B., Kleifges, M., Klute, M., Kobayashi, M., Koke, D., Kopec, A., von Krosigk, B., Kuger, F., LaCascio, L., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, A., Li, S., Liang, S., Liang, Z., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Lucchetti, G. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Maier, B., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Menéndez, J., Messina, M., Milosovic, B., Milutinovic, S., Miuchi, K., Miyata, R., Molinario, A., Monteiro, C. M. B., Morå, K., Moriyama, S., Morteau, E., Mosbacher, Y., Müller, J., Murra, M., Newstead, J. L., Ni, K., O'Hare, C., Oberlack, U., Obradovic, M., Ostrowskiy, I., Ouahada, S., Paetsch, B., Pan, Y., Pandurovic, M., Pellegrini, Q., Peres, R., Piastra, F., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qiao, K., Qin, J., Rajado, M., García, D. Ramírez, Ravindran, A., Razeto, A., Sanchez, L., Sanchez-Lucas, P., Sartorelli, G., Scaffidi, A., Schreiner, J., Schulte, P., Eißing, H. Schulze, Schumann, M., Schwenck, A., Schwenk, A., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Sharma, S., Shen, W., Shi, S. Y., Shimada, T., Simgen, H., Singh, R., Solmaz, M., Stanley, O., Steidl, M., Stevens, A., Takeda, A., Tan, P. -L., Thers, D., Thümmler, T., Tönnies, F., Toschi, F., Trinchero, G., Trotta, R., Tunnell, C. D., Urquijo, P., Utoyama, M., Valerius, K., Vecchi, S., Vetter, S., Volta, G., Vorkapic, D., Wang, W., Weerman, K. M., Weinheimer, C., Weiss, M., Wenz, D., Wilson, M., Wittweg, C., Wolf, J., Wu, V. H. S., Wüstling, S., Wurm, M., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., Zhong, M., Zuber, K.
We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-ton scale liquid Xenon-based direct detection experiment, DARWIN. We tr
Externí odkaz:
http://arxiv.org/abs/2410.00755
Autor:
Arasteh, Soroosh Tayebi, Lotfinia, Mahshad, Perez-Toro, Paula Andrea, Arias-Vergara, Tomas, Orozco-Arroyave, Juan Rafael, Schuster, Maria, Maier, Andreas, Yang, Seung Hee
Speech pathology has impacts on communication abilities and quality of life. While deep learning-based models have shown potential in diagnosing these disorders, the use of sensitive data raises critical privacy concerns. Although differential privac
Externí odkaz:
http://arxiv.org/abs/2409.19078
Autor:
Christodoulou, Evangelia, Reinke, Annika, Houhou, Rola, Kalinowski, Piotr, Erkan, Selen, Sudre, Carole H., Burgos, Ninon, Boutaj, Sofiène, Loizillon, Sophie, Solal, Maëlys, Rieke, Nicola, Cheplygina, Veronika, Antonelli, Michela, Mayer, Leon D., Tizabi, Minu D., Cardoso, M. Jorge, Simpson, Amber, Jäger, Paul F., Kopp-Schneider, Annette, Varoquaux, Gaël, Colliot, Olivier, Maier-Hein, Lena
Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be translated into clinical practice. Frequently, broad conclusions are simply derived from mean performance values. I
Externí odkaz:
http://arxiv.org/abs/2409.17763
Autor:
Rokuss, Maximilian, Kirchhoff, Yannick, Roy, Saikat, Kovacs, Balint, Ulrich, Constantin, Wald, Tassilo, Zenk, Maximilian, Denner, Stefan, Isensee, Fabian, Vollmuth, Philipp, Kleesiek, Jens, Maier-Hein, Klaus
Accurate segmentation of Multiple Sclerosis (MS) lesions in longitudinal MRI scans is crucial for monitoring disease progression and treatment efficacy. Although changes across time are taken into account when assessing images in clinical practice, m
Externí odkaz:
http://arxiv.org/abs/2409.13416
Autor:
Mihajlovic, Marko, Prokudin, Sergey, Tang, Siyu, Maier, Robert, Bogo, Federica, Tung, Tony, Boyer, Edmond
Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method, gaining populari
Externí odkaz:
http://arxiv.org/abs/2409.11211
Autor:
Cremers, Jolien, Kohler, Benjamin, Maier, Benjamin Frank, Eriksen, Stine Nymann, Einsiedler, Johanna, Christensen, Frederik Kølby, Lehmann, Sune, Lassen, David Dreyer, Mortensen, Laust Hvas, Bjerre-Nielsen, Andreas
Social networks shape individuals' lives, influencing everything from career paths to health. This paper presents a registry-based, multi-layer and temporal network of the entire Danish population in the years 2008-2021 (roughly 7.2 mill. individuals
Externí odkaz:
http://arxiv.org/abs/2409.11099
Autor:
Bai, Jieyun, Zhou, Zihao, Ou, Zhanhong, Koehler, Gregor, Stock, Raphael, Maier-Hein, Klaus, Elbatel, Marawan, Martí, Robert, Li, Xiaomeng, Qiu, Yaoyang, Gou, Panjie, Chen, Gongping, Zhao, Lei, Zhang, Jianxun, Dai, Yu, Wang, Fangyijie, Silvestre, Guénolé, Curran, Kathleen, Sun, Hongkun, Xu, Jing, Cai, Pengzhou, Jiang, Lu, Lan, Libin, Ni, Dong, Zhong, Mei, Chen, Gaowen, Campello, Víctor M., Lu, Yaosheng, Lekadir, Karim
Segmentation of the fetal and maternal structures, particularly intrapartum ultrasound imaging as advocated by the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) for monitoring labor progression, is a crucial first step for
Externí odkaz:
http://arxiv.org/abs/2409.10980
Autor:
Kovacs, Balint, Xiao, Shuhan, Rokuss, Maximilian, Ulrich, Constantin, Isensee, Fabian, Maier-Hein, Klaus H.
The third autoPET challenge introduced a new data-centric task this year, shifting the focus from model development to improving metastatic lesion segmentation on PET/CT images through data quality and handling strategies. In response, we developed t
Externí odkaz:
http://arxiv.org/abs/2409.10120