Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Khudorozhkov, Roman"'
In recent years, Deep Neural Networks were successfully adopted in numerous domains to solve various image-related tasks, ranging from simple classification to fine borders annotation. Naturally, many researches proposed to use it to solve geological
Externí odkaz:
http://arxiv.org/abs/2001.06416
Over the last few years, Convolutional Neural Networks (CNNs) were successfully adopted in numerous domains to solve various image-related tasks, ranging from simple classification to fine borders annotation. Tracking seismic horizons is no different
Externí odkaz:
http://arxiv.org/abs/2001.03390
In this work we apply variations of ResNet architecture to the task of atrial fibrillation classification. Variations differ in number of filter after first convolution, ResNet block layout, number of filters in block convolutions and number of ResNe
Externí odkaz:
http://arxiv.org/abs/1810.00396
Autor:
Kuvaev, Alexander, Khudorozhkov, Roman
The article focuses on determining the predictive uncertainty of a model on the example of atrial fibrillation detection problem by a single-lead ECG signal. To this end, the model predicts parameters of the beta distribution over class probabilities
Externí odkaz:
http://arxiv.org/abs/1807.09312
One of the problems on the way to successful implementation of neural networks is the quality of annotation. For instance, different annotators can annotate images in a different way and very often their decisions do not match exactly and in extreme
Externí odkaz:
http://arxiv.org/abs/1807.09151
Autor:
Illarionov, Egor, Khudorozhkov, Roman
State-of-the-art machine learning algorithms demonstrate close to absolute performance in selected challenges. We provide arguments that the reason can be in low variability of the samples and high effectiveness in learning typical patterns. Due to t
Externí odkaz:
http://arxiv.org/abs/1804.02543
Autor:
Khudorozhkov Roman, Sorokina Svetlana, Kozhevin Alexey, Koryagin Aleksander, Tsimfer Sergey, Goryachev Stepan
Publikováno v:
First Break. 39:51-56
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::069e852e2064918ff894aeda6233fb6e
https://doi.org/10.3997/1365-2397.fb2021052
https://doi.org/10.3997/1365-2397.fb2021052
Autor:
Kohei Arai, Supriya Kapoor
This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held