3 papers
cs.CV2019
Examining the Capability of GANs to Replace Real Biomedical Images in Classification Models Training
Vassili Kovalev, Siarhei Kazlouski
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…
cs.CV2019
Influence of Control Parameters and the Size of Biomedical Image Datasets on the Success of Adversarial Attacks
Vassili Kovalev, Dmitry Voynov
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.…
cs.CV2018
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
Mitko Veta, Yujing J. Heng, Nikolas Stathonikos +30
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 an…