1. P. Riya, K. Nakulraj, and A. Anusha, "Pothole Detection Methods," in 2018 3rd International Conference on Inventive Computation Technologies (ICICT), 2018: IEEE, pp. 120-123. [ DOI:10.1109/ICICT43934.2018.9034440] 2. Y.-M. Kim, Y.-G. Kim, S.-Y. Son, S.-Y. Lim, B.-Y. Choi, and D.-H. Choi, "Review of Recent Automated Pothole-Detection Methods," Applied Sciences, vol. 12, no. 11, 2022, doi: 10.3390/app12115320. [ DOI:10.3390/app12115320] 3. W. S. Qureshi et al., "An Exploration of Recent Intelligent Image Analysis Techniques for Visual Pavement Surface Condition Assessment," Sensors (Basel), vol. 22, no. 22, Nov 21 2022, doi: 10.3390/s22229019. [ DOI:10.3390/s22229019] 4. K. R and N. S, "Pothole and Object Detection for an Autonomous Vehicle Using YOLO," presented at the 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), 2021. 5. S. Sen et al., "Pothole Detection System Using Object Detection through Dash Cam Video Feed," presented at the 2023 International Conference for Advancement in Technology (ICONAT), 2023. [ DOI:10.1109/ICONAT57137.2023.10080856] 6. M. Sathvik, G. Saranya, and S. Karpagaselvi, "An Intelligent Convolutional Neural Network based Potholes Detection using Yolo-V7," presented at the 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS), 2022. [ DOI:10.1109/ICACRS55517.2022.10029263] 7. D. Chen, N. Chen, X. Zhang, and Y. Guan, "Real-Time Road Pothole Mapping Based on Vibration Analysis in Smart City," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6972-6984, 2022, doi: 10.1109/jstars.2022.3200147. [ DOI:10.1109/JSTARS.2022.3200147] 8. P. M. Harikrishnan and V. P. Gopi, "Vehicle Vibration Signal Processing for Road Surface Monitoring," IEEE Sensors Journal, vol. 17, no. 16, pp. 5192-5197, 2017, doi: 10.1109/jsen.2017.2719865. [ DOI:10.1109/JSEN.2017.2719865] 9. C. G. Harris and J. Pike, "3D positional integration from image sequences," Image and Vision Computing, vol. 6, no. 2, pp. 87-90, 1988. [ DOI:10.1016/0262-8856(88)90003-0] 10. H. C. Longuet-Higgins, "A computer algorithm for reconstructing a scene from two projections," Nature, vol. 293, no. 5828, pp. 133-135, 1981. [ DOI:10.1038/293133a0] 11. Aparna, Y. Bhatia, R. Rai, V. Gupta, N. Aggarwal, and A. Akula, "Convolutional neural networks based potholes detection using thermal imaging," Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 3, pp. 578-588, 2022, doi: 10.1016/j.jksuci.2019.02.004. [ DOI:10.1016/j.jksuci.2019.02.004] 12. S. Gupta, P. Sharma, D. Sharma, V. Gupta, and N. Sambyal, "Detection and localization of potholes in thermal images using deep neural networks," Multimedia Tools and Applications, vol. 79, no. 35-36, pp. 26265-26284, 2020, doi: 10.1007/s11042-020-09293-8. [ DOI:10.1007/s11042-020-09293-8] 13. J. Terven, D.-M. Córdova-Esparza, and J.-A. Romero-González, "A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas," Machine Learning and Knowledge Extraction, vol. 5, no. 4, pp. 1680-1716, 2023. [ DOI:10.3390/make5040083] 14. M. Gao, X. Wang, S. Zhu, and P. Guan, "Detection and segmentation of cement concrete pavement pothole based on image processing technology," Mathematical Problems in Engineering, vol. 2020, no. 1, p. 1360832, 2020. [ DOI:10.1155/2020/1360832] 15. I. Scholl, T. Aach, T. M. Deserno, and T. Kuhlen, "Challenges of medical image processing," Computer science-Research and development, vol. 26, pp. 5-13, 2011. [ DOI:10.1007/s00450-010-0146-9] 16. Y. Bhatia, R. Rai, V. Gupta, N. Aggarwal, and A. Akula, "Convolutional neural networks based potholes detection using thermal imaging," Journal of King Saud University-Computer and Information Sciences, vol. 34, no. 3, pp. 578-588, 2022. [ DOI:10.1016/j.jksuci.2019.02.004] 17. S. Patra, A. I. Middya, and S. Roy, "PotSpot: Participatory sensing based monitoring system for pothole detection using deep learning," Multimedia Tools and Applications, vol. 80, no. 16, pp. 25171-25195, 2021. [ DOI:10.1007/s11042-021-10874-4] 18. R. Sathya and B. Saleena, "A framework for designing unsupervised pothole detection by integrating feature extraction using deep recurrent neural network," Wireless Personal Communications, vol. 126, no. 2, pp. 1241-1271, 2022. [ DOI:10.1007/s11277-022-09790-z] 19. R. Fan, U. Ozgunalp, Y. Wang, M. Liu, and I. Pitas, "Rethinking road surface 3-d reconstruction and pothole detection: From perspective transformation to disparity map segmentation," IEEE Transactions on Cybernetics, vol. 52, no. 7, pp. 5799-5808, 2021. [ DOI:10.1109/TCYB.2021.3060461] 20. P. Jiang, D. Ergu, F. Liu, Y. Cai, and B. Ma, "A Review of Yolo algorithm developments," Procedia computer science, vol. 199, pp. 1066-1073, 2022. [ DOI:10.1016/j.procs.2022.01.135] 21. C. Wan, Y. Pang, and S. Lan, "Overview of YOLO Object Detection Algorithm," International Journal of Computing and Information Technology, vol. 2, no. 1, pp. 11-11, 2022. [ DOI:10.56028/ijcit.1.2.11] 22. M. Nazarkevych and N. Oleksiv, "Оbject recognition system based on the Yolo model and database formation," Ukrainian Journal of Information Technology, vol. 6, pp. 120-126, 01/01 2024, doi: 10.23939/ujit2024.01.120. [ DOI:10.23939/ujit2024.01.120] 23. B. Karthika, M. Dharssinee, V. Reshma, R. Venkatesan, and R. Sujarani, "Object Detection Using YOLO-V8," in 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2024: IEEE, pp. 1-4. [ DOI:10.1109/ICCCNT61001.2024.10724411] 24. B. P, P. P, D. M, and V. S, "Unauthorized Drone Detection Using Deep Learning," International Journal for Research in Applied Science and Engineering Technology, vol. 12, no. 5, pp. 282-287, 2024, doi: 10.22214/ijraset.2024.61496. [ DOI:10.22214/ijraset.2024.61496] 25. F. Imanuel, S. K. Waruwu, A. Linardy, and A. M. Husein, "Literature review application of yolo algorithm for detection and tracking," Journal of Computer Networks, Architecture and High Performance Computing, vol. 6, no. 3, pp. 1378-1383, 2024. [ DOI:10.47709/cnahpc.v6i3.4374] 26. C. Altuntas, "Triangulation and time-of-flight based 3D digitisation techniques of cultural heritage structures," The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 43, pp. 825-830, 2021. [ DOI:10.5194/isprs-archives-XLIII-B2-2021-825-2021] 27. "pothoe dataset." https://roboflow.com/ (accessed. 28. W. Song, X. Xie, G. Li, and Z. Wang, "Flexible method to calibrate projector-camera systems with high accuracy," Electronics Letters, vol. 50, no. 23, pp. 1685-1687, 2014, doi: 10.1049/el.2014.1383. [ DOI:10.1049/el.2014.1383] 29. Z. Zhang, "A flexible new technique for camera calibration," IEEE Transactions on pattern analysis and machine intelligence, vol. 22, no. 11, pp. 1330-1334, 2000. [ DOI:10.1109/34.888718]
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