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All issues Volume 399 (2023) E3S Web Conf., 399 (2023) 04020 References
Open Access
Issue
E3S Web Conf.
Volume 399, 2023
International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
Article Number 04020
Number of page(s) 8
Section Computer Science
DOI https://doi.org/10.1051/e3sconf/202339904020
Published online 12 July 2023
  1. Broughton George, Jiří Janota, Jan Blaha, Tomáš Rouček, Maxim Simon, Tomáš Vintr, Tao Yang, Zhi Yan, and Tomáš Krajník. 2022. “Embedding Weather Simulation in Auto-Labelling Pipelines Improves vehicles Detection in Adverse Conditions.” Sensors 22 (22). https://doi.org/10.3390/s22228855. [Google Scholar]
  2. Chaudhary Sarika, Pooja Nagpal, and Yomesh Devgan. 2020. “AI BASED TRAFFIC AND AUTOMOBILE MONITORING SYSTEM.” International Journal of Innovative Research in Computer Science & Technology. https://doi.org/10.21276/ijircst.2020.8.3.2. [Google Scholar]
  3. Dohnal Filip, Martin Hubacek, and Katerina Simkova. 2019. “Detection of Microrelief Objects to Impede the Movement of vehicles in Terrain.” ISPRS International Journal of Geo-Information. https://doi.org/10.3390/ijgi8030101. [Google Scholar]
  4. Fastiuk Yevhen, Lviv Polytechnic National University, Ruslan Bachynskyy, and Nataliia Huzynets. 2021a. “Methods of vehicles Recognition and Detecting Traffic Rules Violations on Motion Picture Based on OpenCV Framework.” Advances in Cyber-Physical Systems. https://doi.org/10.23939/acps2021.02.105. [Google Scholar]
  5. Pal’o, J., J. Caban, M. Kiktová, and E. Černický. 2021b. “Methods of vehicles Recognition and Detecting Traffic Rules Violations on Motion Picture Based on OpenCV Framework.” Advances in Cyber-Physical Systems. https://doi.org/10.23939/acps2021.02.105. [Google Scholar]
  6. Gupta, Brij B., and Nadia Nedjah. 2020. Safety, Security, and Reliability of Robotic Systems: Algorithms, Applications, and Technologies. CRC Press. [Google Scholar]
  7. Hala, A. M. A. Ba, A.M. Ba Hala, and Belgorod State National Research University. 2020. “ON DETECTION OF UNMANNED AERIAL vehicles.” Research Result. Information Technologies. https://doi.org/10.18413/2518-1092-2020-5-4-0-2. [Google Scholar]
  8. Kremer Philipp, and Sangyoung Park. 2021. “Detection and Mitigation of Safety Critical Lane Changes in Partially-Connected vehicles.” 2021 IEEE Intelligent vehicles Symposium (IV). https://doi.org/10.1109/iv48863.2021.9575629. [Google Scholar]
  9. Li Da, Bodong Liang, and Weigang Zhang. 2014. “Real-Time Moving vehicles Detection, Tracking, and Counting System Implemented with OpenCV.” 2014 4th IEEE International Conference on Information Science and Technology. https://doi.org/10.1109/icist.2014.6920557. [Google Scholar]
  10. Li Shuang, Faliang Chang, and Chunsheng Liu. 2021a. “Bi-Directional Dense Traffic Counting Based on Spatio-Temporal Counting Feature and Counting- LSTM Network.” IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2020.3001638. [Google Scholar]
  11. Shopa, P., N. Sumitha, and P. S. K. Patra. 2021b. “Bi-Directional Dense Traffic Counting Based on Spatio-Temporal Counting Feature and Counting-LSTM Network.” IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2020.3001638. [Google Scholar]
  12. Meimban Raymond Joseph, Alexa Ray Fernando, Armil Monsura, Jonrey Ranada, and J.C. Apduhan. 2018a. “Blood Cells Counting Using Python OpenCV.” 2018 14th IEEE International Conference on Signal Processing (ICSP). https://doi.org/10.1109/icsp.2018.8652384. [Google Scholar]
  13. Giblin, James M., and Walter H. Kraft. 2018b. “Blood Cells Counting Using Python OpenCV.” 2018 14th IEEE International Conference on Signal Processing (ICSP). https://doi.org/10.1109/icsp.2018.8652384. [Google Scholar]
  14. Mou, Xiaozheng. n.d. “Vision Based Obstacle Detection and Mapping for Unmanned Surface vehicles.” https://doi.org/10.32657/10356/73653. [Google Scholar]
  15. Oldenziel Emilio, Lars Ohnemus, and Sascha Saralajew. 2020. “Provident Detection of vehicles at Night.” 2020 IEEE Intelligent vehicles Symposium (IV). https://doi.org/10.1109/iv47402.2020.9304752. [Google Scholar]
  16. Pavlic Mario, Heidrun Belzner, Gerhard Rigoll, and Slobodan Ilic. 2012. “Image Based Fog Detection in vehicles.” 2012 IEEE Intelligent vehicles Symposium. https://doi.org/10.1109/ivs.2012.6232256. [Google Scholar]
  17. “Road vehicles. Detection of Exhaust Systems Leaks. Helium Test Method and Detection Device Specification.” n.dhttps://doi.org/10.3403/30095558. [Google Scholar]
  18. Shopa, P., N. Sumitha, and P. S. K. Patra. 2014a. “Traffic Sign Detection and Recognition Using OpenCV.” International Conference on Information Communication and Embedded Systems (ICICES2014). https://doi.org/10.1109/icices.2014.7033810. [Google Scholar]
  19. Ligus, Slawek. 2014b. “Traffic Sign Detection and Recognition Using OpenCV.” International Conference on Information Communication and Embedded Systems (ICICES2014). https://doi.org/10.1109/icices.2014.7033810. [Google Scholar]
  20. Soryal Joseph, and Tarek Saadawi. 2013. “DoS Attack Detection in Internet- Connected vehicles.” 2013 International Conference on Connected vehicles and Expo (ICCVE). https://doi.org/10.1109/iccve.2013.6799761. [Google Scholar]
  21. Woo Joo, Ji-Hyeon Baek, So-Hyeon Jo, Sun Young Kim, and Jae-Hoon Jeong. 2022. “A Study on Object Detection Performance of YOLOv4 for Autonomous Driving of Tram.” Sensors 22 (22). https://doi.org/10.3390/s22229026. [PubMed] [Google Scholar]
  22. Xie Hongbin, Yubo Liu, Haoming An, Jiafeng Yi, Chao Li, Xing Wang, and Wei Chai. 2022. “Recent Advances in Prevention, Detection and Treatment in Prosthetic Joint Infections of Bioactive Materials.” Frontiers in Bioengineering and Biotechnology 10 (November): 1053399. [CrossRef] [PubMed] [Google Scholar]

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