Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Kovalev, Vassili"'
Vertical Federated Learning (VFL) is a privacy-preserving distributed learning paradigm where different parties collaboratively learn models using partitioned features of shared samples, without leaking private data. Recent research has shown promisi
Externí odkaz:
http://arxiv.org/abs/2405.17495
Examining the Capability of GANs to Replace Real Biomedical Images in Classification Models Training
Autor:
Kovalev, Vassili, Kazlouski, Siarhei
In this paper, we explore the possibility of generating artificial biomedical images that can be used as a substitute for real image datasets in applied machine learning tasks. We are focusing on generation of realistic chest X-ray images as well as
Externí odkaz:
http://arxiv.org/abs/1904.08688
Autor:
Kovalev, Vassili, Voynov, Dmitry
In this paper, we study dependence of the success rate of adversarial attacks to the Deep Neural Networks on the biomedical image type, control parameters, and image dataset size. With this work, we are going to contribute towards accumulation of exp
Externí odkaz:
http://arxiv.org/abs/1904.06964
Autor:
Veta, Mitko, Heng, Yujing J., Stathonikos, Nikolas, Bejnordi, Babak Ehteshami, Beca, Francisco, Wollmann, Thomas, Rohr, Karl, Shah, Manan A., Wang, Dayong, Rousson, Mikael, Hedlund, Martin, Tellez, David, Ciompi, Francesco, Zerhouni, Erwan, Lanyi, David, Viana, Matheus, Kovalev, Vassili, Liauchuk, Vitali, Phoulady, Hady Ahmady, Qaiser, Talha, Graham, Simon, Rajpoot, Nasir, Sjöblom, Erik, Molin, Jesper, Paeng, Kyunghyun, Hwang, Sangheum, Park, Sunggyun, Jia, Zhipeng, Chang, Eric I-Chao, Xu, Yan, Beck, Andrew H., van Diest, Paul J., Pluim, Josien P. W.
Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is highly subjective and labor-intensive task. Previous efforts to automate tumor proliferati
Externí odkaz:
http://arxiv.org/abs/1807.08284
Publikováno v:
In Chemometrics and Intelligent Laboratory Systems 15 August 2021 215
Autor:
Veta, Mitko, Heng, Yujing J., Stathonikos, Nikolas, Bejnordi, Babak Ehteshami, Beca, Francisco, Wollmann, Thomas, Rohr, Karl, Shah, Manan A., Wang, Dayong, Rousson, Mikael, Hedlund, Martin, Tellez, David, Ciompi, Francesco, Zerhouni, Erwan, Lanyi, David, Viana, Matheus, Kovalev, Vassili, Liauchuk, Vitali, Phoulady, Hady Ahmady, Qaiser, Talha, Graham, Simon, Rajpoot, Nasir, Sjöblom, Erik, Molin, Jesper, Paeng, Kyunghyun, Hwang, Sangheum, Park, Sunggyun, Jia, Zhipeng, Chang, Eric I-Chao, Xu, Yan, Beck, Andrew H., van Diest, Paul J., Pluim, Josien P.W.
Publikováno v:
In Medical Image Analysis May 2019 54:111-121
Autor:
Ionescu, Bogdan, Müller, Henning, Peteri, Renaud, Dang Nguyen, Duc Tien, Piras, Luca, Riegler, Michael, Tran, Minh Triet, Lux, Mathias, Gurrin, Cathal, Cid, Yashin Dicente, Liauchuk, Vitali, Kovalev, Vassili, Ben Abacha, Asma, Hasan, Sadid A., Datla, Vivek, Liu, Joey, Demner-Fushman, Dina, Pelka, Obioma, Friedrich, C., Chamberlain, Jon, Clark, Adrian, de Herrera, Alba Garcia Seco, Garcia, Narciso, Kavallieratou, Ergina, del Blanco, Carlos Roberto, Rodriguez, Carlos Cuevas, Vasillopoulos, Nikos, Karampidis, Konstantinos
Externí odkaz:
http://hdl.handle.net/1956/23300
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
In Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods 2023:155-178
Autor:
Filipovich, Ihar, Kovalev, Vassili
Publikováno v:
In Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods 2023:179-195