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Akademický článek

FABRIKx: Tackling the Inverse Kinematics Problem of Continuum Robots with Variable Curvature

Autor: Dmitrii Kolpashchikov, Olga Gerget, Viacheslav Danilov

Publikováno v: Robotics, Vol 11, Iss 6, p 128 (2022)

A continuum robot is a unique type of robots which move because of the elastic deformation of their bodies. The kinematics of such robots is typically described using constant curvature assumption. Such an assumption, however, does not completely des

Externí odkaz: https://doaj.org/article/3002cde0325e4b5d9e7aadd44196f0bf

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Convolutional Neural Networks for Biplane X-ray Radioscopy Image Analysis in Cardiac Surgery Instrument Navigation System

Autor: Pavel Sirenko, Sergey Zhariy, Nikolay Fedotov, Danil Maurer, Olga Gerget, Alexey Buller

Publikováno v: 2022 Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b764874e1e2b8ce3cb811633b2d13f8f
https://doi.org/10.1109/usbereit56278.2022.9923362

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Analysis of Deep Neural Networks for Detection of Coronary Artery Stenosis

Autor: K. Yu. Klyshnikov, Viacheslav V. Danilov, Alejandro F. Frangi, Olga Gerget, Evgeny A. Ovcharenko

Publikováno v: Programming and Computer Software. 47:153-160

This paper describes an approach based on machine learning technology that is of particular interest for the localization and characterization of both single focal stenoses and multivessel multifocal lesions. Due to the complexity of analyzing large

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8107c7fc607997af3520eeabab95003c
https://doi.org/10.1134/s0361768821030038

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BOOSTING SEGMENTATION ACCURACY OF THE DEEP LEARNING MODELS BASED ON THE SYNTHETIC DATA GENERATION

Autor: N. V. Laptev, Olga Gerget, L. A. Hérnandez-Gómez, V. V. Danilov, R. A. Manakov, Dmitrii Yu. Kolpashchikov, M. J. Ledesma-Carbayo, F. Alvarez

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIV-2-W1-2021, Pp 33-40 (2021)
Scopus-Elsevier

In the era of data-driven machine learning algorithms, data represents a new oil. The application of machine learning algorithms shows they need large heterogeneous datasets that crucially are correctly labeled. However, data collection and its label

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51fec3bb6a1f778fd1b88cecc83f8638
https://doi.org/10.5194/isprs-archives-xliv-2-w1-2021-33-2021

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GENERATING A LOCAL MAP TO TRAIN NAVIGATION AGENTS IN UNKNOWN ENVIRONMENTS

Autor: Olga Gerget, V.V. Laptev, N.V. Laptev

Publikováno v: Mathematical Methods in Technologies and Technics. :71-77

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::965f874b718f1fee4719a95e7dce2ec8
https://doi.org/10.52348/2712-8873_mmtt_2021_6_71

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METHODS AND ALGORITHMS FOR IMAGE SEGMENTATION

Autor: Karina Jo, Olga Gerget

Publikováno v: Automation and modeling in design and management. 2020:11-16

This study aim to find the optimal segmentation method for detecting brain tumors. For this purpose, the main methods from each group were selected: from stochastic-the method of cluster analysis of k-means, from structural-morphological, from mixed

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b4437800e88944ee0e71c4ac2ef357ea
https://doi.org/10.30987/2658-6436-2020-2-11-16

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RESEARCH OF GENERATIVE ADVERSARIAL NETWORKS FOR THE SYNTHESIS OF NEW MEDICAL DATA

Autor: Vyacheslav Danilov, Olga Gerget, Vladislav V. Laptev

Publikováno v: Automation and modeling in design and management. 2020:17-23

The paper considers the development of a Generative Adversarial Network (GAN) for the synthesis of new medical data. The developed GAN consists of two models trained simultaneously: a generative model (G - Generator), estimating the distribution of d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8c8bd87ca0069e3d2d181862a21c2399
https://doi.org/10.30987/2658-6436-2020-2-17-23

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Segmentation Based on Propagation of Dynamically Changing Superpixels

Autor: D. Yu. Kolpashchikov, Viacheslav Danilov, Olga Gerget, I. P. Skirnevskiy, R. A. Manakov

Publikováno v: Programming and Computer Software. 46:195-206

This paper describes a new method for medical data segmentation based on superpixel propagation. The proposed method is a modification of the classical region growing algorithm and partly inherits the concept of octrees. The key difference of the pro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::28b763abf0221da27154df81e10ec3d9
https://doi.org/10.1134/s0361768820030044

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