Zobrazeno 1 - 10
of 209
pro vyhledávání: '"Röttger, Richard"'
Autor:
Burankova, Yuliya, Abele, Miriam, Bakhtiari, Mohammad, von Törne, Christine, Barth, Teresa, Schweizer, Lisa, Giesbertz, Pieter, Schmidt, Johannes R., Kalkhof, Stefan, Müller-Deile, Janina, van Veelen, Peter A, Mohammed, Yassene, Hammer, Elke, Arend, Lis, Adamowicz, Klaudia, Laske, Tanja, Hartebrodt, Anne, Frisch, Tobias, Meng, Chen, Matschinske, Julian, Späth, Julian, Röttger, Richard, Schwämmle, Veit, Hauck, Stefanie M., Lichtenthaler, Stefan, Imhof, Axel, Mann, Matthias, Ludwig, Christina, Kuster, Bernhard, Baumbach, Jan, Zolotareva, Olga
Quantitative mass spectrometry has revolutionized proteomics by enabling simultaneous quantification of thousands of proteins. Pooling patient-derived data from multiple institutions enhances statistical power but raises significant privacy concerns.
Externí odkaz:
http://arxiv.org/abs/2407.15220
Autor:
Krawczyk, Konrad, Chelkowski, Tadeusz, Laydon, Daniel J, Mishra, Swapnil, Xifara, Denise, Flaxman, Seth, Mellan, Thomas, Schwämmle, Veit, Röttger, Richard, Hadsund, Johannes T, Bhatt, Samir
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 6, p e28253 (2021)
BackgroundBefore the advent of an effective vaccine, nonpharmaceutical interventions, such as mask-wearing, social distancing, and lockdowns, have been the primary measures to combat the COVID-19 pandemic. Such measures are highly effective when ther
Externí odkaz:
https://doaj.org/article/b1cf25a8bf9341f3a8beab140d55ea39
Autor:
Conde, Marcos V., Timofte, Radu, Huang, Yibin, Peng, Jingyang, Chen, Chang, Li, Cheng, Pérez-Pellitero, Eduardo, Song, Fenglong, Bai, Furui, Liu, Shuai, Feng, Chaoyu, Wang, Xiaotao, Lei, Lei, Zhu, Yu, Li, Chenghua, Jiang, Yingying, A, Yong, Wang, Peisong, Leng, Cong, Cheng, Jian, Liu, Xiaoyu, Yin, Zhicun, Zhang, Zhilu, Li, Junyi, Liu, Ming, Zuo, Wangmeng, Jiang, Jun, Kim, Jinha, Zhang, Yue, Zou, Beiji, Zong, Zhikai, Liu, Xiaoxiao, Vega, Juan Marín, Sloth, Michael, Schneider-Kamp, Peter, Röttger, Richard, Kınlı, Furkan, Özcan, Barış, Kıraç, Furkan, Leyi, Li, Uddin, SM Nadim, Ghosh, Dipon Kumar, Jung, Yong Ju
Cameras capture sensor RAW images and transform them into pleasant RGB images, suitable for the human eyes, using their integrated Image Signal Processor (ISP). Numerous low-level vision tasks operate in the RAW domain (e.g. image denoising, white ba
Externí odkaz:
http://arxiv.org/abs/2210.11153
Autor:
Hartebrodt, Anne, Röttger, Richard
Federated learning (FL) is a privacy-aware data mining strategy keeping the private data on the owners' machine and thereby confidential. The clients compute local models and send them to an aggregator which computes a global model. In hybrid FL, the
Externí odkaz:
http://arxiv.org/abs/2210.06163
We introduce DRHDR, a Dual branch Residual Convolutional Neural Network for Multi-Bracket HDR Imaging. To address the challenges of fusing multiple brackets from dynamic scenes, we propose an efficient dual branch network that operates on two differe
Externí odkaz:
http://arxiv.org/abs/2206.04124
Autor:
Pérez-Pellitero, Eduardo, Catley-Chandar, Sibi, Shaw, Richard, Leonardis, Aleš, Timofte, Radu, Zhang, Zexin, Liu, Cen, Peng, Yunbo, Lin, Yue, Yu, Gaocheng, Zhang, Jin, Ma, Zhe, Wang, Hongbin, Chen, Xiangyu, Wang, Xintao, Wu, Haiwei, Liu, Lin, Dong, Chao, Zhou, Jiantao, Yan, Qingsen, Zhang, Song, Chen, Weiye, Liu, Yuhang, Zhang, Zhen, Zhang, Yanning, Shi, Javen Qinfeng, Gong, Dong, Zhu, Dan, Sun, Mengdi, Chen, Guannan, Hu, Yang, Li, Haowei, Zou, Baozhu, Liu, Zhen, Lin, Wenjie, Jiang, Ting, Jiang, Chengzhi, Li, Xinpeng, Han, Mingyan, Fan, Haoqiang, Sun, Jian, Liu, Shuaicheng, Marín-Vega, Juan, Sloth, Michael, Schneider-Kamp, Peter, Röttger, Richard, Li, Chunyang, Bao, Long, He, Gang, Xu, Ziyao, Xu, Li, Zhan, Gen, Sun, Ming, Wen, Xing, Li, Junlin, Li, Jinjing, Li, Chenghua, Gang, Ruipeng, Li, Fangya, Liu, Chenming, Feng, Shuang, Lei, Fei, Liu, Rui, Ruan, Junxiang, Dai, Tianhong, Li, Wei, Lu, Zhan, Liu, Hengyan, Huang, Peian, Ren, Guangyu, Luo, Yonglin, Liu, Chang, Tu, Qiang, Ma, Sai, Cao, Yizhen, Tel, Steven, Heyrman, Barthelemy, Ginhac, Dominique, Lee, Chul, Kim, Gahyeon, Park, Seonghyun, Vien, An Gia, Mai, Truong Thanh Nhat, Yoon, Howoon, Vo, Tu, Holston, Alexander, Zaheer, Sheir, Park, Chan Y.
Publikováno v:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022
This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set
Externí odkaz:
http://arxiv.org/abs/2205.12633
Federated learning (FL) is emerging as a privacy-aware alternative to classical cloud-based machine learning. In FL, the sensitive data remains in data silos and only aggregated parameters are exchanged. Hospitals and research institutions which are
Externí odkaz:
http://arxiv.org/abs/2205.12109
Autor:
Hozakowska-Roszkowska, Dominika Marzena, Mengel-From, Jonas, Hristozova, Teodora K., Pedersen, Jacob Krabbe, Jeune, Bernard, Andersen-Ranberg, Karen, Hjelmborg, Jacob V.B., Christensen, Kaare, Röttger, Richard, Nygaard, Marianne
Publikováno v:
In Mechanisms of Ageing and Development December 2024 222
Autor:
Retzlaff, Carl O., Angerschmid, Alessa, Saranti, Anna, Schneeberger, David, Röttger, Richard, Müller, Heimo, Holzinger, Andreas
Publikováno v:
In Cognitive Systems Research August 2024 86
Autor:
Matschinske, Julian, Späth, Julian, Nasirigerdeh, Reza, Torkzadehmahani, Reihaneh, Hartebrodt, Anne, Orbán, Balázs, Fejér, Sándor, Zolotareva, Olga, Bakhtiari, Mohammad, Bihari, Béla, Bloice, Marcus, Donner, Nina C, Fdhila, Walid, Frisch, Tobias, Hauschild, Anne-Christin, Heider, Dominik, Holzinger, Andreas, Hötzendorfer, Walter, Hospes, Jan, Kacprowski, Tim, Kastelitz, Markus, List, Markus, Mayer, Rudolf, Moga, Mónika, Müller, Heimo, Pustozerova, Anastasia, Röttger, Richard, Saranti, Anna, Schmidt, Harald HHW, Tschohl, Christof, Wenke, Nina K, Baumbach, Jan
Machine Learning (ML) and Artificial Intelligence (AI) have shown promising results in many areas and are driven by the increasing amount of available data. However, this data is often distributed across different institutions and cannot be shared du
Externí odkaz:
http://arxiv.org/abs/2105.05734