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International Journal of Robotics and Automation Technology

Articles

Vol. 11 (2024)

Computer Vision Based Areal Photographic Rocket Detection using YOLOv8 Models

DOI
https://doi.org/10.31875/2409-9694.2024.11.03
Submitted
September 9, 2024
Published
09.09.2024

Abstract

Advances in aerospace engineering and aerodynamics have pioneered space exploration and helped support telecommunication infrastructure. But these same developments have also aided in the creation of weapons of devastating impact. This necessitates the development of ways for detecting and tracking rockets. While several methods, mostly based on Doppler radar exist, the need for active radio emissions limits the applicability of these systems. A passive system has several advantages over traditional techniques, however their potential is largely unexplored. This work seeks to tackle this research gap by exploring the potential of emerging computer vision townies applied to rocket detection and tracking. The advantages of such a system are the relatively low cost as well as passive nature making observation stations harder to detect and easier to deploy. This work explores the potential of pre-trained, lightweight YOLOv8 architectures for rocket detection in real-world situations. A publicly available dataset is utilized and a comparative analysis is carried out between nano and small models. Both models demonstrate favorable outcomes with an accuracy of 0.90 for rocket body detection and 0.93 for engine flame detection. Nevertheless, rocket detection into space is still difficult, with a precision of 0.64 for this class. This paper indicates areas for additional refinement and demonstrates the potential of computer vision technology in passive rocket detection.

References

  1. Malanowski M, Borowiec K, Rzewuski S, Kulpa K. Detection of supersonic rockets using passive bistatic radar. IEEE Aerospace and Electronic Systems Magazine 2018; 33(1): 24-33. https://doi.org/10.1109/MAES.2017.160198
  2. Stone ML, Banner GP. Radars for the detection and tracking of ballistic missiles, satellites, and planets. Lincoln laboratory Journal 2000; 12(2): 217-244./
  3. Idhis SM, Dawdi T, Nasir Q, Talib MA, Omran Y. Detection and localization of unmanned aerial vehicles based on radar technology. In: Bianchini M, Piuri V, Das S, Shaw RN. (Eds.) Advanced Computing and Intelligent Technologies. Springer, Singapore 2022; pp. 429-452. https://doi.org/10.1007/978-981-16-2164-2_34
  4. Wang C, Tian J, Cao J, Wang X. Deep learning-based uav detection in pulse-doppler radar. IEEE Transactions on Geoscience and Remote Sensing 2022; 60: 1-12. https://doi.org/10.1109/TGRS.2021.3104907
  5. Karamanavis V, Dirks H, Fuhrmann L, Schlichthaber F, Egli N, Patzelt T, Klare J. Characterization of deorbiting satellites and space debris with radar. Advances in Space Research 2023; 72(8): 3269-3281. https://doi.org/10.1016/j.asr.2023.07.033
  6. Banerjee C, Nguyen K, Fookes C, George K. Physics-informed computer vision: A review and perspectives. ACM Comput Surv 2024. https://doi.org/10.1145/3689037
  7. Liang L, Ma H, Zhao L, Xie X, Hua C, Zhang M, Zhang Y. Vehicle detection algorithms for autonomous driving: A review. Sensors 2024; 24(10). https://doi.org/10.3390/s24103088
  8. Farid A, Hussain F, Khan K, Shahzad M, Khan U, Mahmood Z. A fast and accurate real-time vehicle detection method using deep learning for unconstrained environments. Applied Sciences 2023; 13(5). https://doi.org/10.3390/app13053059
  9. He C, Saha P. Investigating YOLO Models Towards Outdoor Obstacle Detection For Visually Impaired People 2023. https://doi.org/10.21203/rs.3.rs-3733857/v1
  10. Petrovic A, Bacanin N, Jovanovic L, Cadjenovic J, Kaljevic J, Zivkovic M, Antonijevic M. Computer-vision unmanned aerial vehicle detection system using yolov8 architectures. International Journal of Robotics and Automation Technology 2024; 11: 1-12. https://doi.org/10.31875/2409-9694.2024.11.01
  11. Jovanovic L, Bacanin N, Zivkovic M, Mani J, Strumberger I, Antonijevic M. Comparison of yolo architectures for face mask detection in images. In: 2023 16th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS), IEEE 2023; pp. 179-182. https://doi.org/10.1109/TELSIKS57806.2023.10316138
  12. Milanovic A, Jovanovic L, Zivkovic M, Bacanin N, Cajic M, Antonijevic M. Exploring pre-trained model potential for reflective vest real time detection with yolov8 models. In: 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), IEEE 2024; pp. 1210-1216. https://doi.org/10.1109/ICAAIC60222.2024.10575617
  13. Jankovic P, Protic M, Jovanovic L, Bacanin N, Zivkovic M, Kaljevic J. Yolov8 utilization in occupational health and safety. In: 2024 Zooming Innovation in Consumer Technologies Conference (ZINC), IEEE 2024; pp. 182-187. https://doi.org/10.1109/ZINC61849.2024.10579310
  14. Protic M, Jovanovic L, Dobrojevic M, Cajic M, Zivkovic M, Shaker H, Bacanin N. Signals intelligence based drone detection using yolov8 models 2024. https://doi.org/10.2991/978-94-6463-482-2_6
  15. Djuric M, Jovanovic L, Zivkovic M, Bacanin N, Antonijevic M, Sarac M. The adaboost approach tuned by sns metaheuristics for fraud detection. In: Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences: PCCDS 2022. Springer 2023; pp. 115-128. https://doi.org/10.1007/978-981-19-8742-7_10
  16. Stankovic M, Jovanovic L, Antonijevic M, Bozovic A, Bacanin N, Zivkovic M. Univariate individual household energy forecasting by tuned long short-term memory network. In: Inventive Systems and Control: Proceedings of ICISC 2023. Springer 2023; pp. 403-417. https://doi.org/10.1007/978-981-99-1624-5_30
  17. Cincovic J, Jovanovic L, Nikolic B, Bacanin N. Neurodegenerative condition detection using modified metaheuristic for attention based recurrent neural networks and extreme gradient boosting tuning. IEEE Access 2024; 12: 26719-26734. https://doi.org/10.1109/ACCESS.2024.3367588
  18. Kozakijevic S, Jovanovic L, Babic L, Kaljevic J, Zivkovic M, Bacanin N. Machine learning for company review sentiment analysis interpretation. In: International Conference on Multi-Strategy Learning Environment. Springer 2024; pp. 647-659. https://doi.org/10.1007/978-981-97-1488-9_47
  19. Jovanovic L, Bacanin N, Ravikumar R, Antonijevic M, Radic G, Zivkovic M. Generative adversarial networks for synthetic training data replacement in phishing email detection using natural language processing. In: International Conference on Smart Data Intelligence. Springer 2024; pp. 607-618. https://doi.org/10.1007/978-981-97-3191-6_46
  20. Kumpf K, Protic M, Jovanovic L, Cajic M, Zivkovic M, Bacanin N. Insider threat detection using bidirectional encoder representations from transformers and optimized adaboost classifier. In: 2024 International Conference on Circuit, Systems and Communication (ICCSC). IEEE 2024; pp. 1-6. https://doi.org/10.1109/ICCSC62074.2024.10616526
  21. Salb M, Jovanovic L, Bacanin N, Kunjadic G, Antonijevic M, Zivkovic M, Devi VK. The long short-term memory tuning for multi-step ahead wind energy forecasting using enhanced sine cosine algorithm and variation mode decomposition. In: International Conference on Paradigms of Communication, Computing and Data Analytics. Springer 2023; pp. 31-43. https://doi.org/10.1007/978-981-99-4626-6_3
  22. Jovanovic L, Kljajic M, Petrovic A, Mizdrakovic V, Zivkovic M, Bacanin N. Modified teaching-learning-based algorithm tuned long short-term memory for household energy consumption forecasting. In: International Conference on Worldwide Computing and Its Applications. Springer 1997; pp. 347-362. https://doi.org/10.1007/978-981-99-5881-8_28
  23. Zivkovic M, Jovanovic L, Pavlov M, Bacanin N, Dobrojevic M, Salb M. Optimized recurrent neural networks with attention for wind farm energy generation forecasting. In: 2023 16th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS). IEEE 2023; pp. 187-190. https://doi.org/10.1109/TELSIKS57806.2023.10316047
  24. Bozovic A, Jovanovic L, Desnica E, Radovanovic L, Zivkovic M, Bacanin N. Direct current motor malfunction detection through metastatic optimized audio analysis and classification. In: 2024 International Conference on Inventive Computation Technologies (ICICT). IEEE 2024; pp. 1471-1478. https://doi.org/10.1109/ICICT60155.2024.10544852
  25. Jovanovic L, Bacanin N, Simic V, Pamucar D, Zivkovic M. Audio analysis speeding detection techniques based on metaheuristic-optimized machine learning models. Engineering Applications of Artificial Intelligence 2024; 133: 108463. https://doi.org/10.1016/j.engappai.2024.108463
  26. Babic L, Jovanovic L, Petrovic A, Zivkovic M, Zivkovic T, Bacanin N. Leveraging metaheuristic optimized machine learning classifiers to determine employee satisfaction. In: International Conference on Multi-Strategy Learning Environment. Springer 2024; pp. 337-352. https://doi.org/10.1007/978-981-97-1488-9_26
  27. Jovanovic L, Kljajic M, Mizdrakovic V, Marevic V, Zivkovic M, Bacanin N. Predicting credit card churn: Application of xgboost tuned by modified sine cosine algorithm. In: 2023 3rd International Conference on Smart Data Intelligence (ICSMDI). IEEE 2023; pp. 55-62. https://doi.org/10.1109/ICSMDI57622.2023.00018
  28. Jovanovic L, Zivkovic M, Bacanin N, Dobrojevic M, Simic V, Sadasivuni KK, Tirkolaee EB. Evaluating the performance of metaheuristic-tuned weight agnostic neural networks for crop yield prediction. Neural Computing and Applications 2024; 1-30. https://doi.org/10.1007/s00521-024-09850-4
  29. Todorovic M, Petrovic A, Toskovic A, Zivkovic M, Jovanovic L, Bacanin N. Multivariate bitcoin price prediction based on lstm tuned by hybrid reptile search algorithm. In: 2023 16th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS). IEEE 2023; pp. 195-198. https://doi.org/10.1109/TELSIKS57806.2023.10316108
  30. Jovanovic L, Gajevic M, Dobrojevic M, Budimirovic N, Bacanin N, Zivkovic M. Tackling iot security challenge by metaheuristics tuned extreme learning machine. In: International Conference on Intelligent Sustainable Systems. Springer 2023; pp. 507-522. https://doi.org/10.1007/978-981-99-1726-6_39
  31. Golubovic S, Jovanovic L, Radomirovic B, Njegus A, Zivkovic M, Bacanin N. Evolving deep neural network architectures by sine cosine algorithm for healthcare 4.0. In: 2023 IEEE International Conference on Contemporary Computing and Communications (InC4). IEEE 2023; vol. 1: pp. 1-6. https://doi.org/10.1109/InC457730.2023.10263180
  32. Radomirovic B, Jovanovic L, Stoean C, Zivkovic M, Njegus A, Bacanin N. Solar flare classification using modified metaheuristic optimized xgboost. In: 2023 25th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE 2023; pp. 287-292. https://doi.org/10.1109/SYNASC61333.2023.00049
  33. Bozovic A, Jovanovic L, Desnica E, Bacanin N, Zivkovic M, Antonijevic M, Mani JP. Metaheuristic optimized extreme gradient boosting milling maintenance prediction. In: Congress on Intelligent Systems. Springer 2023; pp. 361-374. https://doi.org/10.1007/978-981-99-9037-5_28
  34. Bisevac P, Toskovic A, Salb M, Jovanovic L, Petrovic A, Zivkovic M, Bacanin N. Solar flare classification via modified metaheuristic optimized extreme gradient boosting. In: International Conference for Information and Communication Technologies. Springer 2023; pp. 81-95. https://doi.org/10.1007/978-3-031-62624-1_7
  35. Mani J, Shaker H, Jovanovic L, et al. Sunspot occurrence forecasting with metaheuristic optimized recurrent neural networks. Theoretical and Applied Computational Intelligence 2023; 1(1): 15-26. https://doi.org/10.31181/taci1120231
  36. Jovanovic L, Jovanovic D, Antonijevic M, Zivkovic M, Budimirovic N, Strumberger I, Bacanin N. The xgboost tuning by improved firefly algorithm for network intrusion detection. In: 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE 2022; pp. 268-275. https://doi.org/10.1109/SYNASC57785.2022.00050
  37. Jovanovic L, Hajdarevic Z, Jovanovic D, Jassim HS, Strumberger I, Bacanin N, Zivkovic M, Antonijevic M. Tuning extreme learning machine by hybrid planet optimization algorithm for diabetes classification. In: Congress on Intelligent Systems. Springer 2022; pp. 23-36. https://doi.org/10.1007/978-981-19-9379-4_3
  38. Jovanovic L, Petrovic A, Zivkovic T, Antonijevic M, Bacanin N, Zivkovic M. Exploring the potential of generative adversarial networks for synthetic medical data generation. In: 2023 31st Telecommunications Forum (TELFOR). IEEE 2023; pp. 1-4. https://doi.org/10.1109/TELFOR59449.2023.10372727
  39. Zivkovic M, Vesic A, Bacanin N, Strumberger I, Antonijevic M, Jovanovic L, Marjanovic M. An improved animal migration optimization approach for extreme learning machine tuning. In: International Conference on Intelligent and Fuzzy Systems. Springer 2022; pp. 3-13. https://doi.org/10.1007/978-3-031-09176-6_1
  40. Jovanovic L, Bacanin N, Antonijevic M, Tuba E, Ivanovic M, Venkatachalam K. Plant classification using firefly algorithm and support vector machine. In: 2022 IEEE Zooming Innovation in Consumer Technologies Conference (ZINC). IEEE 2022; pp. 255-260. https://doi.org/10.1109/ZINC55034.2022.9840579
  41. Cuk A, Bezdan T, Jovanovic L, Antonijevic M, Stankovic M, Simic V, Zivkovic M, Bacanin N. Tuning attention based long-short term memory neural networks for parkinson’s disease detection using modified metaheuristics. Scientific Reports 2024; 14(1): 4309. https://doi.org/10.1038/s41598-024-54680-y
  42. Jovanovic L, Bacanin N, Zivkovic M, Antonijevic M, Jovanovic B, Sretenovic MB, Strumberger I. Machine learning tuning by diversity oriented firefly metaheuristics for industry 4.0. Expert Systems 2024; 41(2): 13293. https://doi.org/10.1111/exsy.13293
  43. Jovanovic L, Bacanin N, Jovancai A, Jovanovic D, Singh D, Antonijevic M, Zivkovic M, Strumberger I. Oil price prediction approach using long shortterm memory network tuned by improved seagull optimization algorithm. In: International Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering & Technology. Springer 2022; pp. 253-265. https://doi.org/10.1007/978-981-99-1431-9_20
  44. Jovanovic L, Strumberger I, Bacanin N, Zivkovic M, Antonijevic M, Bisevac P. Tuned long short-term memory model for ethereum price forecasting via an arithmetic optimization algorithm. International Journal of Hybrid Intelligent Systems 2023; 19(1, 2): 27-43. https://doi.org/10.3233/HIS-230003
  45. Jovanovic L, Damaˇseviˇcius R, Matic R, Kabiljo M, Simic V, Kunjadic G, Antonijevic M, Zivkovic M, Bacanin N. Detecting parkinson’s disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics. Peer J Computer Science 2024; 10: 2031. https://doi.org/10.7717/peerj-cs.2031
  46. Bacanin N, Jovanovic L, Stoean R, Stoean C, Zivkovic M, Antonijevic M, Dobrojevic M. Respiratory condition detection using audio analysis and convolutional neural networks optimized by modified metaheuristics. Axioms 2024; 13(5): 335. https://doi.org/10.3390/axioms13050335
  47. Salb M, Jovanovic L, Bacanin N, Antonijevic M, Zivkovic M, Budimirovic N, Abualigah L. Enhancing internet of things network security using hybrid cnn and xgboost model tuned via modified reptile search algorithm. Applied Sciences 2023; 13(23): 12687. https://doi.org/10.3390/app132312687
  48. Jiang P, Ergu D, Liu F, Cai Y, M, B. A review of yolo algorithm developments. The 8th International Conference on Information Technology and Quantitative Management (ITQM 2020 & 2021): Developing Global Digital Economy after COVID-19. Procedia Computer Science 2022; 199: 1066-1073. https://doi.org/10.1016/j.procs.2022.01.135
  49. Wang C-Y, Yeh I-H, Liao H-YM. YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information 2024.
  50. NASASpaceflight: Rocket Detect Dataset. Roboflow. visited on 2024-08-11 2023. https://universe.roboflow.com/ nasaspaceflight/rocket-detect

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