|
|
|
Список литературы
|
|
|
1. |
Liu S, Yang Q, Cai H, Yan M, Zhang M, Wu D, Xie M, “Market reform of Yunnan electricity in southwestern China: Practice, challenges and implications”, Renew Sust Energ Rev, 113 (2019), 109265 |
2. |
Manfreda S, McCabe MF, Miller PE, Lucas R, Madrigal VP, Mallinis G, Ben Dor E, Helman D, Estes L, Ciraolo G, Müllerová J, Tauro F, De Lima MI, De Lima JLMP, Maltese A, Frances F, Caylor K, Kohv M, Perks M, Ruiz-Pérez G, Su Z, Vico G, Toth B, “On the use of unmanned aerial systems for environmental monitoring”, Remote Sens, 10:4 (2018), 641 |
3. |
Ventura D, Bonifazi A, Gravina MF, Belluscio A, Ardizzone G, “Mapping and classification of ecologically sensitive marine habitats using unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA)”, Remote Sens, 10:9 (2018), 1331 |
4. |
Rusnák M, Sládek J, Kidová A, Lehotský M, “Template for high-resolution river landscape mapping using UAV technology”, Measurement, 115 (2018), 139–151 |
5. |
Langhammer J, Vacková T, “Detection and mapping of the geomorphic effects of flooding using UAV photogrammetry”, Pure Appl Geophys, 175:9 (2018), 3223–3245 |
6. |
James MR, Chandler JH, Eltner A, Fraser C, Miller PE, Mills JP, Noble T, Robson S, Lane SN, “Guidelines on the use of structure-from-motion photogrammetry in geomorphic research”, Earth Surf Process Landf, 44:10 (2019), 2081–2084 |
7. |
Dyson J, Mancini A, Frontoni E, Zingaretti P, “Deep learning for soil and crop segmentation from remotely sensed data”, Remote Sens, 11:16 (2019), 1859 |
8. |
Popescu D, Stoican F, Stamatescu G, Ichim L, Dragana C, “Advanced UAV–WSN system for intelligent monitoring in precision agriculture”, Sensors, 20:3 (2020), 817 |
9. |
Constantin A, Dinculescu R-N, “UAV development and impact in the power system”, 2019 8th Int Conf on Modern Power Systems (MPS), 2019, 1–5 |
10. |
Rafique SF, Bodla MK, Ahmed Z, Nasir U, Zaidi A, Saleem M, “Design and implementation of a UAV for power system utility inspection”, 2014 16th Int Power Electronics and Motion Control Conf and Exposition, 2014, 1146–1150 |
11. |
Addabbo P, Angrisano A, Bernardi ML, Gagliarde G, Mennella A, Nisi M, Ullo SL, “UAV system for photovoltaic plant inspection”, IEEE Aerosp Electron Syst Mag, 33:8 (2018), 58–67 |
12. |
Li L, “The UAV intelligent inspection of transmission lines”, Proceedings of the international conference on advances in mechanical engineering and industrial informatics, Atlantis Press, 2015, 1542–1545 |
13. |
Toth J, Gilpin-Jackson A, “Smart view for a smart grid – Unmanned Aerial Vehicles for transmission lines”, 2010 1st Int Conf on Applied Robotics for the Power Industry, 2010, 1–6 |
14. |
Zormpas A, Moirogiorgou K, Kalaitzakis K, Plokamakis GA, Partsinevelos P, Giakos G, Zervakis M, “Power transmission lines inspection using properly equipped unmanned aerial vehicle (UAV)”, 2018 IEEE Int Conf on Imaging Systems and Techniques (IST), 2018, 1–5 |
15. |
He T, Zeng Y, Hu Z, “Research of multi-rotor UAVs detailed autonomous inspection technology of transmission lines based on route planning”, IEEE Access, 7 (2019), 114955–114965 |
16. |
Guo S, Bai Q, Zhou X, “Foreign object detection of transmission lines based on faster R-CNN”, Information science and applications, eds. Kim KJ, Kim H-Y, Springer Nature Singapore Pte Ltd, Singapore, 2020, 269–275 |
17. |
Yao N, Zhu L, “A novel foreign object detection algorithm based on GMM and K-means for power transmission line inspection”, J Phys Conf Ser, 1607 (2020), 012014 |
18. |
Li J, Nie Y, Cui W, Liu R, Zheng Z, “Power transmission line foreign object detection based on improved YOLOv3 and deployed to the chip”, 2020 3rd Int Conf on Machine Learning and Machine Intelligence, Association for Computing Machinery, 2020, 100–104 |
19. |
Song Y, Zhou Z, Li Q, Chen Y, Xiang P, Yu Q, Zhang L, Lu Y, “Intrusion detection of foreign objects in high-voltage lines based on YOLOv4”, 2021 6th Int Conf on Intelligent Computing and Signal Processing (ICSP), 2021, 1295–1300 |
20. |
Wang Q, Si G, Qu K, Gong J, Cui L, “Transmission line foreign body fault detection using multi-feature fusion based on modified YOLOv5”, J Phys Conf Ser, 2320 (2022), 012028 |
21. |
Xing L, Fan X, Dong Y, Xiong Z, Xing L, Yang Y, Bai H, Zhou C, “Multi-UAV cooperative system for search and rescue based on YOLOv5”, Int J Disaster Risk Reduct, 76 (2022), 102972 |
22. |
Wang C-Y, Bochkovskiy A, Liao H-YM, YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors, 2022, arXiv: 2207.02696 |