Zobrazeno 1 - 10
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pro vyhledávání: '"Schilling, Marcel P."'
Autor:
Graham, Simon, Vu, Quoc Dang, Jahanifar, Mostafa, Weigert, Martin, Schmidt, Uwe, Zhang, Wenhua, Zhang, Jun, Yang, Sen, Xiang, Jinxi, Wang, Xiyue, Rumberger, Josef Lorenz, Baumann, Elias, Hirsch, Peter, Liu, Lihao, Hong, Chenyang, Aviles-Rivero, Angelica I., Jain, Ayushi, Ahn, Heeyoung, Hong, Yiyu, Azzuni, Hussam, Xu, Min, Yaqub, Mohammad, Blache, Marie-Claire, Piégu, Benoît, Vernay, Bertrand, Scherr, Tim, Böhland, Moritz, Löffler, Katharina, Li, Jiachen, Ying, Weiqin, Wang, Chixin, Kainmueller, Dagmar, Schönlieb, Carola-Bibiane, Liu, Shuolin, Talsania, Dhairya, Meda, Yughender, Mishra, Prakash, Ridzuan, Muhammad, Neumann, Oliver, Schilling, Marcel P., Reischl, Markus, Mikut, Ralf, Huang, Banban, Chien, Hsiang-Chin, Wang, Ching-Ping, Lee, Chia-Yen, Lin, Hong-Kun, Liu, Zaiyi, Pan, Xipeng, Han, Chu, Cheng, Jijun, Dawood, Muhammad, Deshpande, Srijay, Bashir, Raja Muhammad Saad, Shephard, Adam, Costa, Pedro, Nunes, João D., Campilho, Aurélio, Cardoso, Jaime S., S, Hrishikesh P, Puthussery, Densen, G, Devika R, C V, Jiji, Zhang, Ye, Fang, Zijie, Lin, Zhifan, Zhang, Yongbing, Lin, Chunhui, Zhang, Liukun, Mao, Lijian, Wu, Min, Vo, Vi Thi-Tuong, Kim, Soo-Hyung, Lee, Taebum, Kondo, Satoshi, Kasai, Satoshi, Dumbhare, Pranay, Phuse, Vedant, Dubey, Yash, Jamthikar, Ankush, Vuong, Trinh Thi Le, Kwak, Jin Tae, Ziaei, Dorsa, Jung, Hyun, Miao, Tianyi, Snead, David, Raza, Shan E Ahmed, Minhas, Fayyaz, Rajpoot, Nasir M.
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest
Externí odkaz:
http://arxiv.org/abs/2303.06274
Publikováno v:
Schulte, H. Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022. KIT Scientific Publishing, 2022
Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and developers have to implement complete solutions which are often instal
Externí odkaz:
http://arxiv.org/abs/2211.14417
Autor:
Böhland, Moritz, Neumann, Oliver, Schilling, Marcel P., Reischl, Markus, Mikut, Ralf, Löffler, Katharina, Scherr, Tim
Automated cell nucleus segmentation and classification are required to assist pathologists in their decision making. The Colon Nuclei Identification and Counting Challenge 2022 (CoNIC Challenge 2022) supports the development and comparability of segm
Externí odkaz:
http://arxiv.org/abs/2202.13960
Autor:
Schilling, Marcel P., Rettenberger, Luca, Münke, Friedrich, Cui, Haijun, Popova, Anna A., Levkin, Pavel A., Mikut, Ralf, Reischl, Markus
Publikováno v:
Proceedings - 31. Workshop Computational Intelligence, 2021
Recent research in the field of computer vision strongly focuses on deep learning architectures to tackle image processing problems. Deep neural networks are often considered in complex image processing scenarios since traditional computer vision app
Externí odkaz:
http://arxiv.org/abs/2111.13970
Autor:
Isele, Simon T., Schilling, Marcel P., Klein, Fabian E., Saralajew, Sascha, Zoellner, J. Marius
Research on localization and perception for Autonomous Driving is mainly focused on camera and LiDAR datasets, rarely on radar data. Manually labeling sparse radar point clouds is challenging. For a dataset generation, we propose the cross sensor Rad
Externí odkaz:
http://arxiv.org/abs/2012.01993
Akademický článek
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Akademický článek
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Publikováno v:
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 197-200 (2022)
Deep learning is often used for automated diagnosis support in biomedical image processing scenarios. Annotated datasets are essential for the supervised training of deep neural networks. The problem of consistent and noise-free annotation remains fo
Externí odkaz:
https://doaj.org/article/a568d9279ca74186854406b7c3ef2d03
Publikováno v:
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 329-332 (2022)
Modern medical technology offers potential for the automatic generation of datasets that can be fed into deep learning systems. However, even though raw data for supporting diagnostics can be obtained with manageable effort, generating annotations is
Externí odkaz:
https://doaj.org/article/73dbf4d756404c99af86a62cb12e003e
Publikováno v:
Journal of Integrative Bioinformatics, Vol 19, Iss 4, Pp 128-44 (2022)
Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehens
Externí odkaz:
https://doaj.org/article/9e5c426941d541ddb3761db86b104779