# A Road Defect Detection System Using Smartphones
## 3 A Proposed Road Defect Detection System
### A Road Defect Detection with 1D-Cnn
2022R1A5A8026986, 40%), and this paper was supported by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0020536, HRD Program for Industrial Innovation, 10%). Not applicable. The road defect detection dataset is available at [[https://github.com/GyuLimkim/Road_Defect_Dataset/tree/main](https://github.com/GyuLimkim/Road_Defect_Dataset/tree/main)]([https://github.com/GyuLimkim/Road_Defect_Dataset/tree/main](https://github.com/GyuLimkim/Road_Defect_Dataset/tree/main)) (accessed on 21 March 2024). The authors declare no conflicts of interest. ## References

* (1) [PERSON]; [PERSON]; [PERSON] Effect of Combining Algorithms in Smartphone Based Pothole Detection. _Int. J. Parent Res. Technol._**2020**, _14_, 63-72. [CrossRef]
* (2) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] RoADS: A Road Pavement Monitoring System for Anomaly Detection Using Smart Phones. In _International Workshop on Modeling Social Media_; Lecture Notes in Computer Science; Springer International Publishing: Cham, Switzerland, 2016; pp. 128-146. [CrossRef]
* (3) [PERSON]; [PERSON]; [PERSON] Investigation of Pothole Severity and Maintenance Methods in Canada through Questionnaire Survey. _J. Cold Reg. Eng._**2018**, _32_, 04018002. [CrossRef]
* (4) Report Inconvenience in Road Use. Available online: [[https://www.molit.go.kr/USR/WPCG2001/m_235/DTLjsp](https://www.molit.go.kr/USR/WPCG2001/m_235/DTLjsp)]([https://www.molit.go.kr/USR/WPCG2001/m_235/DTLjsp](https://www.molit.go.kr/USR/WPCG2001/m_235/DTLjsp)) (accessed on 8 February 2024). * (5) [PERSON]; [PERSON]; [PERSON] Pothole Detection: An Efficient Vision Based Method Using RGB Color Space Image Segmentation. In Proceedings of the 2017 40 th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, Croatia, 22-26 May 2017. [CrossRef]
* (6) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Pothole Detection Based on Disparity Transformation and Road Surface Modeling. _IEEE Trans. Image Process._**2020**, _29_, 897-908. [CrossRef] [PubMed]
* (7) [PERSON]; [PERSON] Watershed-Based Real-Time Image Processing for Multi-Potholes Detection on Asphalt Road. In Proceedings of the 2019 IEEE 9 th International Conference on System Engineering and Technology (ICSET), Shah Alam, Malaysia, 7 October 2019. [CrossRef]
* (8) [PERSON]; [PERSON] Pothole Classification Model Using Edge Detection in Road Image. _Appl. Sci._**2020**, _10_, 6662. [CrossRef]* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Detection and Localization of Potholes in Thermal Images Using Deep Neural Networks. _Multimed. Tools Appl._**2020**, _79_, 26265-26284. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON] Attention Based Coupled Framework for Road and Pothole Segmentation. In Proceedings of the 2020 25 th International Conference on Pattern Recognition (ICPR), Milan, Italy, 10-15 January 2021. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Convolutional Neural Networks Based Potholes Detection Using Thermal Imaging. _J. King Sautl Univ.-Comput. Inf. Sci._**2019**, _34_, 578-588. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Pothole and Plain Road Classification Using Adaptive Mutation Dipper Thread Optimization and Transfer Learning for Self Driving Cars. _IEEE Access_**2022**, _10_, 84188-84211. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON] Pothole Detection Using Location-Aware Convolutional Neural Networks. _Int. J. Mach. Learn. Cybern._**2020**, _11_, 899-911. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Convolutional Neural Network for Pothole Detection in Asphalt Pavement. _Road Mater. Pavement Des._**2019**, _22_, 42-58. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Stereo-Based 3D Reconstruction of Potholes by a Hybrid, Dense Matching Scheme. _IEEE Sens.