Acceso abierto

Lightweight Low-Altitude UAV Object Detection Based on Improved YOLOv5s


Cite

Zhao F, Zhao C, Guo J.Visual perception-based anti-drone technology: Development dynamics and trend [J]. National Defense Technology, 44(05), 35–45. DOI: 10.13943/j.issn1671-4547.2023.05.05. Zhao F Zhao C Guo J. Visual perception-based anti-drone technology: Development dynamics and trend [J] . National Defense Technology , 44 ( 05 ), 35 45 . DOI: 10.13943/j.issn1671-4547.2023.05.05 . Open DOISearch in Google Scholar

Oh H M, Lee H, Kim M Y .Comparing Convolutional Neural Network(CNN) models for machine learning-based drone and bird classification of anti-drone system [C]//2019 19th International Conference on Control, Automation and Systems (ICCAS).2019. DOI:10.23919/ICCAS47443. 2019. 8971699. Oh H M Lee H Kim M Y. Comparing Convolutional Neural Network(CNN) models for machine learning-based drone and bird classification of anti-drone system [C] // 2019 19th International Conference on Control, Automation and Systems (ICCAS) . 2019 . DOI: 10.23919/ICCAS47443.2019.8971699 . Open DOISearch in Google Scholar

Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation [C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 580–587. Girshick R Donahue J Darrell T Rich feature hierarchies for accurate object detection and semantic segmentation [C] // Proceedings of the IEEE conference on computer vision and pattern recognition . 2014 : 580 587 . Search in Google Scholar

Girshick R. Fast r-cnn [C]//Proceedings of the IEEE international conference on computer vision. 2015: 1440–1448. Girshick R. Fast r-cnn [C] // Proceedings of the IEEE international conference on computer vision . 2015 : 1440 1448 . Search in Google Scholar

Ren S, He K, Girshick R, et al. Faster r-cnn: Towards real-time object detection with region proposal networks [J]. Advances in neural information processing systems, 2015, 28. Ren S He K Girshick R Faster r-cnn: Towards real-time object detection with region proposal networks [J] . Advances in neural information processing systems , 2015 , 28 . Search in Google Scholar

He K, Gkioxari G, Dollár P, et al. Mask r-cnn [C]//Proceedings of the IEEE international conference on computer vision. 2017: 2961–2969. He K Gkioxari G Dollár P Mask r-cnn [C] // Proceedings of the IEEE international conference on computer vision . 2017 : 2961 2969 . Search in Google Scholar

Redmon J, Divvala S, Girshick R, et al. You only look once: Unified, real-time object detection [C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 779–788. Redmon J Divvala S Girshick R You only look once: Unified, real-time object detection [C] // Proceedings of the IEEE conference on computer vision and pattern recognition . 2016 : 779 788 . Search in Google Scholar

Redmon J, Farhadi A. YOLO9000: better, faster, stronger [C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 7263–7271. Redmon J Farhadi A. YOLO9000: better, faster, stronger [C] // Proceedings of the IEEE conference on computer vision and pattern recognition . 2017 : 7263 7271 . Search in Google Scholar

Redmon J, Farhadi A. Yolov3: An incremental improvement [J]. arXiv preprint arXiv:1804.02767, 2018. Redmon J Farhadi A. Yolov3: An incremental improvement [J] . arXiv preprint arXiv:1804.02767 , 2018 . Search in Google Scholar

Liu W, Anguelov D, Erhan D, et al. Ssd: Single shot multibox detector [C]//Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I 14. Springer International Publishing, 2016: 21–37. Liu W Anguelov D Erhan D Ssd: Single shot multibox detector [C] // Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I 14 . Springer International Publishing , 2016 : 21 37 . Search in Google Scholar

LU Q, YU Y Q, XU D M, et al. Improved YOLOv5 Small Drones Target [J]. Computer Science, 2023, 50(S2): 212–219. Lu Q Yu Y Q Xu D M Improved YOLOv5 Small Drones Target [J] . Computer Science , 2023 , 50 ( S2 ): 212 219 . Search in Google Scholar

Yang H Y, Rong Y S, Jian Y H, et al. GCB-YOLOv5s algorithm for real-time detection for a low altitude UAV [J]. Journal of Ordnance Equipment Engineering, 2023, 44(07): 1–8. Yang H Y Rong Y S Jian Y H GCB-YOLOv5s algorithm for real-time detection for a low altitude UAV [J] . Journal of Ordnance Equipment Engineering , 2023 , 44 ( 07 ): 1 8 . Search in Google Scholar

Bao W Q, Xie L Q, Xu C, et al. A Real-time detection method of micro UAV based on YOLOv5 [J]. Journal of Ordnance Equipment Engineering, 2022, 43(05): 232–237. Bao W Q Xie L Q Xu C A Real-time detection method of micro UAV based on YOLOv5 [J] . Journal of Ordnance Equipment Engineering , 2022 , 43 ( 05 ): 232 237 . Search in Google Scholar

Chen J, Kao S, He H, et al. Run, Don’t Walk: Chasing Higher FLOPS for Faster Neural Networks [C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023: 12021–12031. Chen J Kao S He H Run, Don’t Walk: Chasing Higher FLOPS for Faster Neural Networks [C] // Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 2023 : 12021 12031 . Search in Google Scholar

Wang J, Chen K, Xu R, et al. Carafe: Content-aware reassembly of features [C]//Proceedings of the IEEE/CVF international conference on computer vision. 2019: 3007–3016. Wang J Chen K Xu R Carafe: Content-aware reassembly of features [C] // Proceedings of the IEEE/CVF international conference on computer vision . 2019 : 3007 3016 . Search in Google Scholar

Ouyang D, He S, Zhang G, et al. Efficient Multi-Scale Attention Module with Cross-Spatial Learning [C]//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1–5. Ouyang D He S Zhang G Efficient Multi-Scale Attention Module with Cross-Spatial Learning [C] // ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE , 2023 : 1 5 . Search in Google Scholar

Li H, Li J, Wei H, et al. Slim-neck by GSConv: A better design paradigm of detector architectures for autonomous vehicles [J]. arXiv preprint arXiv: 2206.02424, 2022. Li H Li J Wei H Slim-neck by GSConv: A better design paradigm of detector architectures for autonomous vehicles [J] . arXiv preprint arXiv: 2206.02424 , 2022 . Search in Google Scholar

Zheng Y, Chen Z, Lv D, et al. Air-to-Air Visual Detection of Micro-UAVs: An Experimental Evaluation of Deep Learning [J].IEEE Robotics and Automation Letters, 2021, PP(99): 1–1. DOI: 10.1109/LRA. 2021. 3056059. Zheng Y Chen Z Lv D Air-to-Air Visual Detection of Micro-UAVs: An Experimental Evaluation of Deep Learning [J] . IEEE Robotics and Automation Letters , 2021 , PP ( 99 ): 1 1 . DOI: 10.1109/LRA.2021.3056059 . Open DOISearch in Google Scholar

Coluccia A, Fascista A, Schumann A, et al. Drone vs. Bird Detection: Deep Learning Algorithms and Results from a Grand Challenge [J]. Sensors, 2021, 21(8): 2824. DOI:10.3390/s21082824. Coluccia A Fascista A Schumann A Drone vs. Bird Detection: Deep Learning Algorithms and Results from a Grand Challenge [J] . Sensors , 2021 , 21 ( 8 ): 2824 . DOI: 10.3390/s21082824 . Open DOISearch in Google Scholar

Pawelczyk M L, Wojtyra M .Real World Object Detection Dataset for Quadcopter Unmanned Aerial Vehicle Detection [J]. IEEE Access, 8:174394-174409 [2023-10-12]. DOI: 10.1109/ACCESS.2020. 3026192. Pawelczyk M L Wojtyra M. Real World Object Detection Dataset for Quadcopter Unmanned Aerial Vehicle Detection [J] . IEEE Access , 8 : 174394 174409 [2023-10-12]. DOI: 10.1109/ACCESS.2020. 3026192 . Open DOISearch in Google Scholar

Li J, Murray J, Ismaili D, et al. Reconstruction of 3D flight trajectories from ad-hoc camera networks [C]//2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020: 1621–1628. Li J Murray J Ismaili D Reconstruction of 3D flight trajectories from ad-hoc camera networks [C] // 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE , 2020 : 1621 1628 . Search in Google Scholar

J. Zhao, J. Zhang, D. Li and D. Wang, “Vision-Based Anti-UAV Detection and Tracking [J]. IEEE Transactions on Intelligent Transportation Systems, Dec. 2022, DOI: 10.1109/TITS. 2022.3177627. Zhao J. Zhang J. Li D. Wang D. Vision-Based Anti-UAV Detection and Tracking [J] . IEEE Transactions on Intelligent Transportation Systems , Dec . 2022 , DOI: 10.1109/TITS. 2022.3177627 . Open DOISearch in Google Scholar

Jiang Nan, Wang Kuiran, Peng Xiaoke, et al. Anti-UAV: A large multi-modal benchmark for UAV tracking [J]. arXiv preprint arXiv, 2021. 2101(2), 1–13. Nan Jiang Kuiran Wang Xiaoke Peng Anti-UAV: A large multi-modal benchmark for UAV tracking [J] . arXiv preprint arXiv , 2021 . 2101 ( 2 ), 1 13 . Search in Google Scholar

Hu J, Shen L, Sun G. Squeeze-and-excitation networks [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE Press, 2018: 7132–7141. Hu J Shen L Sun G. Squeeze-and-excitation networks [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition , June 18-23 , 2018 , Salt Lake City, UT, USA. New York : IEEE Press , 2018 : 7132 7141 . Search in Google Scholar

Wang Q L, Wu B G, Zhu P F, et al. ECA-net: efficient channel attention for deep convolutional neural networks [C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 13-19, 2020, Seattle, WA, USA. New York: IEEE Press, 2020. Wang Q L Wu B G Zhu P F ECA-net: efficient channel attention for deep convolutional neural networks [C] // 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 13-19 , 2020 , Seattle, WA, USA. New York : IEEE Press , 2020 . Search in Google Scholar

Woo S, Park J, Lee J Y, et al. CBAM: convolutional block attention module [M]//Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science. Cham: Springer, 2018, 11211: 3–19. Woo S Park J Lee J Y CBAM: convolutional block attention module [M]//Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018 . Lecture notes in computer science. Cham: Springer , 2018 , 11211 : 3 19 . Search in Google Scholar

Hou Q B, Zhou D Q, Feng J S. Coordinate attention for efficient mobile network design [C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 20-25, 2021, Nashville, TN, USA. New York: IEEE Press, 2021: 13708–13717. Hou Q B Zhou D Q Feng J S. Coordinate attention for efficient mobile network design [C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 20-25 , 2021 , Nashville, TN, USA. New York : IEEE Press , 2021 : 13708 13717 . Search in Google Scholar

eISSN:
2470-8038
Idioma:
Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Computer Sciences, other