Beilfuss, T., Kortmann, K.-P., Wielitzka, M., Hansen, C., & Ortmaier, T. (2020) Real-Time Classification of Road Type and Condition in Passenger Vehicles. 21st IFAC World Congress (Virtual) Berlin, Germany.Search in Google Scholar
Coadou, Y. (2013) Boosted decision trees and applications. EPJ Web of Conferences, 55. https://doi.org/10.1051/EPJCONF/20135502004Search in Google Scholar
Cutler, A., Cutler, D. R., & Stevens, J. R. (2012) Random Forests. Ensemble Machine Learning, 157–175. https://doi.org/10.1007/978-1-4419-9326-7_5Search in Google Scholar
Departament Infrastruktury. (2019). Informacja o wynikach kontroli. Zapewnienie należytego stanu technicznego nawierzchni dróg krajowych (ang. Information on the results of the inspection. Ensuring proper technical condition of national road surfaces). https://www.nik.gov.pl/plik/id,21157,vp,23789.pdfSearch in Google Scholar
Doniec, R., Piaseczna, N., Li, F., Duraj, K., Pour, H. H., Grzegorzek, M., Mocny-Pachońska, K., & Tkacz, E. (2022) Classification of Roads and Types of Public Roads Using EOG Smart Glasses and an Algorithm Based on Machine Learning While Driving a Car. Electronics 2022, 11(18), 2960. https://doi.org/10.3390/ELECTRONICS11182960Search in Google Scholar
Geiger, A., Lenz, P., Stiller, C., & Urtasun, R. (2013). Vision meets robotics: The KITTI dataset. Http://Dx.Doi.Org/10.1177/0278364913491297, 32(11), 1231–1237. https://doi.org/10.1177/0278364913491297Search in Google Scholar
He, K., Zhang, X., Ren, S., & Sun, J. (2015). Deep Residual Learning for Image Recognition. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016-December, 770–778. https://doi.org/10.48550/arxiv.1512.03385Search in Google Scholar
Hu, J., Shen, L., Albanie, S., Sun, G., & Wu, E. (2017) Squeeze-and-Excitation Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(8), 2011–2023. https://doi.org/10.48550/arxiv.1709.01507Search in Google Scholar
Kowalski, S., Opoka, K., Ciuła, J., Analysis, C. J., & Kowalski, S. (2022) Analysis of the end-of-life the front suspension beam of a vehicle. Eksploatacja i NiEzawodNosc-MaiNtENaNcE aNd REliability, 24(3), 3. https://doi.org/10.17531/ein.2022.3.6Search in Google Scholar
Lei, T., Mohamed, A. A., & Claudel, C. (2018) An IMU-based traffic and road condition monitoring system. HardwareX, e00045. https://doi.org/10.1016/j.ohx.2018.e00045Search in Google Scholar
Mosley, L. (2013). A balanced approach to the multi-class imbalance problem. https://doi.org/10.31274/ETD-180810-3375Search in Google Scholar
Radopoulou, S. C., & Brilakis, I. (2016) Improving Road Asset Condition Monitoring. Transportation Research Procedia, 14, 3004–3012. https://doi.org/10.1016/J.TRPRO.2016.05.436Search in Google Scholar
Rateke, T., Justen, K. A., & Wangenheim, A. von. (2019) Road surface classification with images captured from low-cost camera-road traversing knowledge (RTK) dataset. Revista de Informatica Teorica e Aplicada, 26(3), 50–64. https://doi.org/10.22456/2175-2745.91522Search in Google Scholar
Šabanovič, E., Žuraulis, V., Prentkovskis, O., & Skrickij, V. (2020) Identification of Road-Surface Type Using Deep Neural Networks for Friction Coefficient Estimation. Sensors (Basel, Switzerland), 20(3). https://doi.org/10.3390/S20030612Search in Google Scholar
Shinzato, P. Y., dos Santos, T. C., Rosero, L. A., Ridel, D. A., Massera, C. M., Alencar, F., Batista, M. P., Hata, A. Y., Osório, F. S., & Wolf, D. F. (2016). CaRINA dataset: An emerging-country urban scenario benchmark for road detection systems. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 41–46. https://doi.org/10.1109/ITSC.2016.7795529Search in Google Scholar
STmicroelectronics. (2019) LSM6DSOX Datasheet. iNEMO inertial module: always-on 3D accelerometer and 3D gyroscope. https://www.st.com/resource/en/datasheet/lsm6dsox.pdfSearch in Google Scholar
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017) Attention Is All You Need. Advances in Neural Information Processing Systems, 2017-December, 5999–6009. https://doi.org/10.48550/arxiv.1706.03762Search in Google Scholar
Wang, S., Kodagoda, S., & Ranasinghe, R. (2012) Road Terrain Type Classification based on Laser Measurement System Data. Australasian Conference on Robotics and Automation, Victoria University of Wellington, New Zealand.Search in Google Scholar