Application of Deep Learning Techniques in UAV Image Recognition and Tracking

[1] Chen, C. J., Huang, Y. Y., Li, Y. S., Chen, Y. C., & Huang, Y. M. (2021). Identification of fruit tree pests with deep learning on embedded drone to achieve accurate pesticide spraying. IEEE Access, PP(99), 1-1. Search in Google Scholar

[2] Forkan, A. R. M., Kang, Y. B., Jayaraman, P. P., Liao, K., Kaul, R., & Morgan, G., et al. (2022). Corrdetector: a framework for structural corrosion detection from drone images using ensemble deep learning. Expert Systems with Applications, 193, 116461-. Search in Google Scholar

[3] Singh, M., Aujla, G. S., & Bali, R. S. (2020). A deep learning-based blockchain mechanism for secure internet of drones environment. IEEE Transactions on Intelligent Transportation Systems, PP(99), 1-10. Search in Google Scholar

[4] Jiang, Y., Han, S., & Bai, Y. (2021). (04021092)building and infrastructure defect detection and visualization using drone and deep learning technologies. Journal of Performance of Constructed Facilities(6), 35. Search in Google Scholar

[5] Alkadi, R., Al-Ameri, S., Shoufan, A., & Damiani, E. (2021). Identifying drone operator by deep learning and ensemble learning of imu and control data. IEEE transactions on human-machine systems(51-5). Search in Google Scholar

[6] Cetin, E., Barrado, C., & Pastor, E. (2021). Improving real-time drone detection for counter-drone systems. The Aeronautical journal(Oct. TN.1292), 125. Search in Google Scholar

[7] Zheng, S., Wang, W., Liu, Z., & Wu, Z. (2021). Forest farm fire drone monitoring system based on deep learning and unmanned aerial vehicle imagery. Mathematical Problems in Engineering, 2021. Search in Google Scholar

[8] Deng, S., Li, S., Xie, K., Song, W., & Qin, H. (2021). A global-local self-adaptive network for drone-view object detection. IEEE Transactions on Image Processing. Search in Google Scholar

[9] Wang, L., Song, W., Lan, Y., Wanga, H., & Tang, Y. (2021). A smart droplet detection approach with vision sensing technique for agricultural aviation application. IEEE Sensors Journal, PP(99), 1-1. Search in Google Scholar

[10] Siddiqui, Z. A., & Park, U. (2020). A drone based transmission line components inspection system with deep learning technique. Energies, 13(13), 3348. Search in Google Scholar

[11] Damgaard, C. (2021). Integrating hierarchical statistical models and machine-learning algorithms for ground-truthing drone images of the vegetation: taxonomy, abundance and population ecological models. Remote Sensing(6). Search in Google Scholar

[12] Demir, K., & Vedat Tümen. (2021). Drone-assisted automated plant diseases identification using spiking deep conventional neural learning. Ai Communications, 1. Search in Google Scholar

[13] Bhatnagar, S., Gill, L., & Ghosh, B. (2020). Drone image segmentation using machine and deep learning for mapping raised bog vegetation communities. Remote Sensing, 12(16), 2602. Search in Google Scholar

[14] Speth, S., Goncalves, A., Rigault, B., Suzuki, S., Bouazizi, M., & Matsuo, Y., et al. (2022). Deep learning with rgb and thermal images onboard a drone for monitoring operations. Journal of Field Robotics. Search in Google Scholar

[15] Gumaei, A., Al-Rakhami, M., Hassan, M. M., Pace, P., & Fortino, G. (2021). Deep learning and blockchain with edge computing for 5g-enabled drone identification and flight mode detection. IEEE Network, 35(1), 94-100. Search in Google Scholar

[16] Chouhan, A., Chutia, D., & Aggarwal, S. P. (2023). Deep learning approach for multi-class semantic segmentation of uav images. INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 32(07). Search in Google Scholar

[17] Meng, L., Hirayama, T., & Oyanagi., S. (2018). Underwater-drone with panoramic camera for automatic fish recognition based on deep learning. IEEE Access, 17880-17886. Search in Google Scholar

[18] Itaru, Nagayama, Wakaki, Uehara, Takaya, & Miyazato. (2019). Study on human detection system using deep neural network and alternative learning for autonomous flying drones. IEEJ Transactions on Industry Applications, 139(2), 149-157. Search in Google Scholar

[19] Thodi, B. T., Khan, Z. S., Jabari, S. E., & Monica Menéndez. (2022). Incorporating kinematic wave theory into a deep learning method for high-resolution traffic speed estimation. IEEE transactions on intelligent transportation systems. Search in Google Scholar

[20] Lee, S., Kim, S., & Moon, S. (2022). Development of a car-free street mapping model using an integrated system with unmanned aerial vehicles, aerial mapping cameras, and a deep learning algorithm. Journal of computing in civil engineering(3), 36. Search in Google Scholar

[21] Casalino, G. (2021). Drone deep reinforcement learning: a review. Electronics, 10. Search in Google Scholar

[22] Rohan, A., Rabah, M., & Kim, S. H. (2019). Convolutional neural network-based real-time object detection and tracking for parrot ar drone 2. IEEE Access, PP(99), 1-1. Search in Google Scholar