Zobrazeno 1 - 10
of 17 205
pro vyhledávání: '"Jakab A"'
Autor:
LaBella, Dominic, Schumacher, Katherine, Mix, Michael, Leu, Kevin, McBurney-Lin, Shan, Nedelec, Pierre, Villanueva-Meyer, Javier, Shapey, Jonathan, Vercauteren, Tom, Chia, Kazumi, Al-Salihi, Omar, Leu, Justin, Halasz, Lia, Velichko, Yury, Wang, Chunhao, Kirkpatrick, John, Floyd, Scott, Reitman, Zachary J., Mullikin, Trey, Bagci, Ulas, Sachdev, Sean, Hattangadi-Gluth, Jona A., Seibert, Tyler, Farid, Nikdokht, Puett, Connor, Pease, Matthew W., Shiue, Kevin, Anwar, Syed Muhammad, Faghani, Shahriar, Haider, Muhammad Ammar, Warman, Pranav, Albrecht, Jake, Jakab, András, Moassefi, Mana, Chung, Verena, Aristizabal, Alejandro, Karargyris, Alexandros, Kassem, Hasan, Pati, Sarthak, Sheller, Micah, Huang, Christina, Coley, Aaron, Ghanta, Siddharth, Schneider, Alex, Sharp, Conrad, Saluja, Rachit, Kofler, Florian, Lohmann, Philipp, Vollmuth, Phillipp, Gagnon, Louis, Adewole, Maruf, Li, Hongwei Bran, Kazerooni, Anahita Fathi, Tahon, Nourel Hoda, Anazodo, Udunna, Moawad, Ahmed W., Menze, Bjoern, Linguraru, Marius George, Aboian, Mariam, Wiestler, Benedikt, Baid, Ujjwal, Conte, Gian-Marco, Rauschecker, Andreas M. T., Nada, Ayman, Abayazeed, Aly H., Huang, Raymond, de Verdier, Maria Correia, Rudie, Jeffrey D., Bakas, Spyridon, Calabrese, Evan
The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aims to advance automated segmentation algorithms using the largest known multi-institutional dataset of radiotherapy planning brain MRIs with expert-annotated target
Externí odkaz:
http://arxiv.org/abs/2405.18383
Autor:
LaBella, Dominic, Baid, Ujjwal, Khanna, Omaditya, McBurney-Lin, Shan, McLean, Ryan, Nedelec, Pierre, Rashid, Arif, Tahon, Nourel Hoda, Altes, Talissa, Bhalerao, Radhika, Dhemesh, Yaseen, Godfrey, Devon, Hilal, Fathi, Floyd, Scott, Janas, Anastasia, Kazerooni, Anahita Fathi, Kirkpatrick, John, Kent, Collin, Kofler, Florian, Leu, Kevin, Maleki, Nazanin, Menze, Bjoern, Pajot, Maxence, Reitman, Zachary J., Rudie, Jeffrey D., Saluja, Rachit, Velichko, Yury, Wang, Chunhao, Warman, Pranav, Adewole, Maruf, Albrecht, Jake, Anazodo, Udunna, Anwar, Syed Muhammad, Bergquist, Timothy, Chen, Sully Francis, Chung, Verena, Conte, Gian-Marco, Dako, Farouk, Eddy, James, Ezhov, Ivan, Khalili, Nastaran, Iglesias, Juan Eugenio, Jiang, Zhifan, Johanson, Elaine, Van Leemput, Koen, Li, Hongwei Bran, Linguraru, Marius George, Liu, Xinyang, Mahtabfar, Aria, Meier, Zeke, Moawad, Ahmed W., Mongan, John, Piraud, Marie, Shinohara, Russell Takeshi, Wiggins, Walter F., Abayazeed, Aly H., Akinola, Rachel, Jakab, András, Bilello, Michel, de Verdier, Maria Correia, Crivellaro, Priscila, Davatzikos, Christos, Farahani, Keyvan, Freymann, John, Hess, Christopher, Huang, Raymond, Lohmann, Philipp, Moassefi, Mana, Pease, Matthew W., Vollmuth, Phillipp, Sollmann, Nico, Diffley, David, Nandolia, Khanak K., Warren, Daniel I., Hussain, Ali, Fehringer, Pascal, Bronstein, Yulia, Deptula, Lisa, Stein, Evan G., Taherzadeh, Mahsa, de Oliveira, Eduardo Portela, Haughey, Aoife, Kontzialis, Marinos, Saba, Luca, Turner, Benjamin, Brüßeler, Melanie M. T., Ansari, Shehbaz, Gkampenis, Athanasios, Weiss, David Maximilian, Mansour, Aya, Shawali, Islam H., Yordanov, Nikolay, Stein, Joel M., Hourani, Roula, Moshebah, Mohammed Yahya, Abouelatta, Ahmed Magdy, Rizvi, Tanvir, Willms, Klara, Martin, Dann C., Okar, Abdullah, D'Anna, Gennaro, Taha, Ahmed, Sharifi, Yasaman, Faghani, Shahriar, Kite, Dominic, Pinho, Marco, Haider, Muhammad Ammar, Aristizabal, Alejandro, Karargyris, Alexandros, Kassem, Hasan, Pati, Sarthak, Sheller, Micah, Alonso-Basanta, Michelle, Villanueva-Meyer, Javier, Rauschecker, Andreas M., Nada, Ayman, Aboian, Mariam, Flanders, Adam E., Wiestler, Benedikt, Bakas, Spyridon, Calabrese, Evan
We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axia
Externí odkaz:
http://arxiv.org/abs/2405.09787
Autor:
Li, Hongwei Bran, Navarro, Fernando, Ezhov, Ivan, Bayat, Amirhossein, Das, Dhritiman, Kofler, Florian, Shit, Suprosanna, Waldmannstetter, Diana, Paetzold, Johannes C., Hu, Xiaobin, Wiestler, Benedikt, Zimmer, Lucas, Amiranashvili, Tamaz, Prabhakar, Chinmay, Berger, Christoph, Weidner, Jonas, Alonso-Basant, Michelle, Rashid, Arif, Baid, Ujjwal, Adel, Wesam, Ali, Deniz, Baheti, Bhakti, Bai, Yingbin, Bhatt, Ishaan, Cetindag, Sabri Can, Chen, Wenting, Cheng, Li, Dutand, Prasad, Dular, Lara, Elattar, Mustafa A., Feng, Ming, Gao, Shengbo, Huisman, Henkjan, Hu, Weifeng, Innani, Shubham, Jiat, Wei, Karimi, Davood, Kuijf, Hugo J., Kwak, Jin Tae, Le, Hoang Long, Lia, Xiang, Lin, Huiyan, Liu, Tongliang, Ma, Jun, Ma, Kai, Ma, Ting, Oksuz, Ilkay, Holland, Robbie, Oliveira, Arlindo L., Pal, Jimut Bahan, Pei, Xuan, Qiao, Maoying, Saha, Anindo, Selvan, Raghavendra, Shen, Linlin, Silva, Joao Lourenco, Spiclin, Ziga, Talbar, Sanjay, Wang, Dadong, Wang, Wei, Wang, Xiong, Wang, Yin, Xia, Ruiling, Xu, Kele, Yan, Yanwu, Yergin, Mert, Yu, Shuang, Zeng, Lingxi, Zhang, YingLin, Zhao, Jiachen, Zheng, Yefeng, Zukovec, Martin, Do, Richard, Becker, Anton, Simpson, Amber, Konukoglu, Ender, Jakab, Andras, Bakas, Spyridon, Joskowicz, Leo, Menze, Bjoern
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentat
Externí odkaz:
http://arxiv.org/abs/2405.18435
Autor:
Jakab, Daniel, Deegan, Brian Michael, Sharma, Sushil, Grua, Eoin Martino, Horgan, Jonathan, Ward, Enda, Van De Ven, Pepijn, Scanlan, Anthony, Eising, Ciarán
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems, 2024
In this paper, we provide a survey on automotive surround-view fisheye optics, with an emphasis on the impact of optical artifacts on computer vision tasks in autonomous driving and ADAS. The automotive industry has advanced in applying state-of-the-
Externí odkaz:
http://arxiv.org/abs/2402.12041
Autor:
Payette, Kelly, Steger, Céline, Licandro, Roxane, de Dumast, Priscille, Li, Hongwei Bran, Barkovich, Matthew, Li, Liu, Dannecker, Maik, Chen, Chen, Ouyang, Cheng, McConnell, Niccolò, Miron, Alina, Li, Yongmin, Uus, Alena, Grigorescu, Irina, Gilliland, Paula Ramirez, Siddiquee, Md Mahfuzur Rahman, Xu, Daguang, Myronenko, Andriy, Wang, Haoyu, Huang, Ziyan, Ye, Jin, Alenyà, Mireia, Comte, Valentin, Camara, Oscar, Masson, Jean-Baptiste, Nilsson, Astrid, Godard, Charlotte, Mazher, Moona, Qayyum, Abdul, Gao, Yibo, Zhou, Hangqi, Gao, Shangqi, Fu, Jia, Dong, Guiming, Wang, Guotai, Rieu, ZunHyan, Yang, HyeonSik, Lee, Minwoo, Płotka, Szymon, Grzeszczyk, Michal K., Sitek, Arkadiusz, Daza, Luisa Vargas, Usma, Santiago, Arbelaez, Pablo, Lu, Wenying, Zhang, Wenhao, Liang, Jing, Valabregue, Romain, Joshi, Anand A., Nayak, Krishna N., Leahy, Richard M., Wilhelmi, Luca, Dändliker, Aline, Ji, Hui, Gennari, Antonio G., Jakovčić, Anton, Klaić, Melita, Adžić, Ana, Marković, Pavel, Grabarić, Gracia, Kasprian, Gregor, Dovjak, Gregor, Rados, Milan, Vasung, Lana, Cuadra, Meritxell Bach, Jakab, Andras
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and the Fetal Brain Tissue Annotation (FeTA) Challenge 2021 helped to establ
Externí odkaz:
http://arxiv.org/abs/2402.09463
Variational quantum algorithms are viewed as promising candidates for demonstrating quantum advantage on near-term devices. These approaches typically involve the training of parameterized quantum circuits through a classical optimization loop. Howev
Externí odkaz:
http://arxiv.org/abs/2402.05227
Autor:
Jakab, Daniel, Grua, Eoin Martino, Deegan, Brian Micheal, Scanlan, Anthony, Van De Ven, Pepijn, Eising, Ciarán
The Modulation Transfer Function (MTF) is an important image quality metric typically used in the automotive domain. However, despite the fact that optical quality has an impact on the performance of computer vision in vehicle automation, for many pu
Externí odkaz:
http://arxiv.org/abs/2401.05232
Autor:
Li, Zizhang, Litvak, Dor, Li, Ruining, Zhang, Yunzhi, Jakab, Tomas, Rupprecht, Christian, Wu, Shangzhe, Vedaldi, Andrea, Wu, Jiajun
Learning 3D models of all animals on the Earth requires massively scaling up existing solutions. With this ultimate goal in mind, we develop 3D-Fauna, an approach that learns a pan-category deformable 3D animal model for more than 100 animal species
Externí odkaz:
http://arxiv.org/abs/2401.02400
Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs. However, these approaches generate objects in isolation without any consideration for the scene where they
Externí odkaz:
http://arxiv.org/abs/2312.12419
Although Neural Radiance Fields (NeRFs) have markedly improved novel view synthesis, accurate uncertainty quantification in their image predictions remains an open problem. The prevailing methods for estimating uncertainty, including the state-of-the
Externí odkaz:
http://arxiv.org/abs/2312.02350