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The deep learning based power line defect detection system built on data collected by the cablewalker drone. / Titov, Evgenii
; Limanovskaya, Oksana; Lemekh, Alexandr и др.
SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. стр. 700-704 8958397 (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings).
Результаты исследований: Глава в книге, отчете, сборнике статей › Материалы конференции › Рецензирование
Harvard
Titov, E
, Limanovskaya, O, Lemekh, A & Volkova, D 2019,
The deep learning based power line defect detection system built on data collected by the cablewalker drone. в
SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings., 8958397, SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings, Institute of Electrical and Electronics Engineers Inc., стр. 700-704, 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019, Novosibirsk, Российская Федерация,
21/10/2019.
https://doi.org/10.1109/SIBIRCON48586.2019.8958397APA
Titov, E.
, Limanovskaya, O., Lemekh, A., & Volkova, D. (2019).
The deep learning based power line defect detection system built on data collected by the cablewalker drone. в
SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings (стр. 700-704). [8958397] (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings). Institute of Electrical and Electronics Engineers Inc..
https://doi.org/10.1109/SIBIRCON48586.2019.8958397Vancouver
Author
BibTeX
@inproceedings{14b61de44c664a09b696c0d6828b0e93,
title = "The deep learning based power line defect detection system built on data collected by the cablewalker drone",
keywords = "cablewalker, darknet, deep learning, defect detection, drone, fault detection, image processing, metal wire maintenance, object detection, power line maintenance, ROV, suspension insulators, transmission line, UAV, YOLO",
author = "Evgenii Titov and Oksana Limanovskaya and Alexandr Lemekh and Daria Volkova",
year = "2019",
month = oct,
doi = "10.1109/SIBIRCON48586.2019.8958397",
language = "English",
series = "SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "700--704",
booktitle = "SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings",
address = "United States",
note = "2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 ; Conference date: 21-10-2019 Through 27-10-2019",
}
RIS
TY - GEN
T1 - The deep learning based power line defect detection system built on data collected by the cablewalker drone
AU - Titov, Evgenii
AU - Limanovskaya, Oksana
AU - Lemekh, Alexandr
AU - Volkova, Daria
PY - 2019/10
Y1 - 2019/10
KW - cablewalker
KW - darknet
KW - deep learning
KW - defect detection
KW - drone
KW - fault detection
KW - image processing
KW - metal wire maintenance
KW - object detection
KW - power line maintenance
KW - ROV
KW - suspension insulators
KW - transmission line
KW - UAV
KW - YOLO
UR - http://www.scopus.com/inward/record.url?scp=85079047770&partnerID=8YFLogxK
U2 - 10.1109/SIBIRCON48586.2019.8958397
DO - 10.1109/SIBIRCON48586.2019.8958397
M3 - Conference contribution
AN - SCOPUS:85079047770
T3 - SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
SP - 700
EP - 704
BT - SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
Y2 - 21 October 2019 through 27 October 2019
ER -
