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Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation. / Кугаевских, Александр Владимирович.

Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 719-724 9208069 (Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Кугаевских, АВ 2020, Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation. in Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020., 9208069, Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020, Institute of Electrical and Electronics Engineers Inc., pp. 719-724, 2020 International Russian Automation Conference, RusAutoCon 2020, Sochi, Russian Federation, 06.09.2020. https://doi.org/10.1109/RusAutoCon49822.2020.9208069

APA

Кугаевских, А. В. (2020). Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation. In Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020 (pp. 719-724). [9208069] (Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RusAutoCon49822.2020.9208069

Vancouver

Кугаевских АВ. Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation. In Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 719-724. 9208069. (Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020). doi: 10.1109/RusAutoCon49822.2020.9208069

Author

Кугаевских, Александр Владимирович. / Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation. Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 719-724 (Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020).

BibTeX

@inproceedings{183dcf539bf5469b8435efeb0e0f9fac,
title = "Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation",
abstract = "This article is dedicated to modeling the end-stopped neuron. This type of neuron gives the maximum response at the end of the line and is used to refine the edge. The article provides an overview of different models of end-stopped neurons. I have proposed a simpler and more accurate model of an end-stopped neuron based on the use of Gabor filters in antiphase. For this purpose, the models of simple and complex cells whose output is used in the proposed model are also described. Simple cells are based on the use of a Gabor filter, the parameters of which are also described in this article. The proposed model has shown its effectiveness.",
keywords = "complex cell, edge detection, end-stopped neuron, Gabor filter, neural network, simple cell",
author = "Кугаевских, {Александр Владимирович}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2020 International Russian Automation Conference, RusAutoCon 2020 ; Conference date: 06-09-2020 Through 12-09-2020",
year = "2020",
month = sep,
doi = "10.1109/RusAutoCon49822.2020.9208069",
language = "English",
series = "Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "719--724",
booktitle = "Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020",
address = "United States",

}

RIS

TY - GEN

T1 - Bio-Inspired End-Stopped Neuron Model for the Curves Segmentation

AU - Кугаевских, Александр Владимирович

N1 - Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/9

Y1 - 2020/9

N2 - This article is dedicated to modeling the end-stopped neuron. This type of neuron gives the maximum response at the end of the line and is used to refine the edge. The article provides an overview of different models of end-stopped neurons. I have proposed a simpler and more accurate model of an end-stopped neuron based on the use of Gabor filters in antiphase. For this purpose, the models of simple and complex cells whose output is used in the proposed model are also described. Simple cells are based on the use of a Gabor filter, the parameters of which are also described in this article. The proposed model has shown its effectiveness.

AB - This article is dedicated to modeling the end-stopped neuron. This type of neuron gives the maximum response at the end of the line and is used to refine the edge. The article provides an overview of different models of end-stopped neurons. I have proposed a simpler and more accurate model of an end-stopped neuron based on the use of Gabor filters in antiphase. For this purpose, the models of simple and complex cells whose output is used in the proposed model are also described. Simple cells are based on the use of a Gabor filter, the parameters of which are also described in this article. The proposed model has shown its effectiveness.

KW - complex cell

KW - edge detection

KW - end-stopped neuron

KW - Gabor filter

KW - neural network

KW - simple cell

UR - http://www.scopus.com/inward/record.url?scp=85093930018&partnerID=8YFLogxK

U2 - 10.1109/RusAutoCon49822.2020.9208069

DO - 10.1109/RusAutoCon49822.2020.9208069

M3 - Conference contribution

AN - SCOPUS:85093930018

T3 - Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020

SP - 719

EP - 724

BT - Proceedings - 2020 International Russian Automation Conference, RusAutoCon 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 International Russian Automation Conference, RusAutoCon 2020

Y2 - 6 September 2020 through 12 September 2020

ER -

ID: 25987794