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

Autor: V. V. Danilov, O. M. Gerget, D. Y. Kolpashchikov, N. V. Laptev, R. A. Manakov, L. A. Hérnandez-Gómez, F. Alvarez, M. J. Ledesma-Carbayo

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

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://doaj.org/article/4b26b9e07661492989505383c5c98f5a

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

RAY-BASED SEGMENTATION ALGORITHM FOR MEDICAL IMAGING

Autor: Alejandro F. Frangi, Olga Gerget, I. P. Skirnevskiy, R. A. Manakov, Viacheslav V. Danilov, Dmitrii Yu. Kolpashchikov

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-2-W12, Pp 37-45 (2019)

In this study, we present a segmentation algorithm based on ray casting and border point detection. The algorithm’s main parameter is the number of emitted rays, which defines the resolution of the object’s boundary. The value of this parameter d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51ab498ef697f71ab48196f75f8dc333
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W12/37/2019/isprs-archives-XLII-2-W12-37-2019.pdf

Motion Planning Algorithm for continuum Robots Bending over Obstacles

Autor: N. V. Laptev, Roman Meshcheryakov, R. A. Manakov, Dmitrii Yu. Kolpashchikov, Viacheslav Danilov, Olga Gerget

Publikováno v: 2019 III International Conference on Control in Technical Systems (CTS).

Continuum robots are manipulators able to bend at any point of their structure. This feature allows continuum robots to avoid unwanted collisions in a complicated working area or grasp objects using their body. In this regard, they are used as instru

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b8e6d9e5cde4621f78a5cfcbf1f62ae9
https://doi.org/10.1109/cts48763.2019.8973282

Visual shape and position sensing algorithm for a continuum robot

Autor: N. V. Laptev, R. A. Manakov, I. P. Skirnevskiy, Olga Gerget, Dmitrii Yu. Kolpashchikov, Viacheslav Danilov

Continuum robots represent an actively developing and fast-growing technology in robotics. To successfully implement control and path planning of continuum robots it is important to develop an accurate three-dimensional shape and position sensing alg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bff722943cfdd31677bec200c0dd4918
http://earchive.tpu.ru/handle/11683/57484