Application of Target Detection Technology Based on Embedded Devices and Convolutional Neural Networks in Power Patrol

DOI

10.2991/978-2-494069-51-0_38How to use a DOI?

Keywords

Deep learning; Embedded devices; Convolutional neural networks; Target detection; Power patrol

Abstract

In order to ensure safe, stable and efficient operation of power production, regular inspections of power equipment and transmission lines must be carried out. With the update of power patrol technology, large volumes of inspection data increase manual workload, there is therefore an urgent need for intelligent inspection work. This study briefly describes the current state of research in target detection and power patrol, analyses the challenges of target detection technology in power inspections and explore possible solutions, finally take a look at its future development. It is hoped that this study will provide a useful reference for related research.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yu Gao
PY  - 2022
DA  - 2022/12/09
TI  - Application of Target Detection Technology Based on Embedded Devices and Convolutional Neural Networks in Power Patrol
BT  - Proceedings of the 2022 7th International Conference on Modern Management and Education Technology (MMET 2022)
PB  - Atlantis Press
SP  - 279
EP  - 284
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-51-0_38
DO  - 10.2991/978-2-494069-51-0_38
ID  - Gao2022
ER  -