[1] Pendar, M.-R., Rodrigues, F., Páscoa, J. C., Lima, R. Review of Coating and Curing Processes: Evaluation in Automotive Industry. Physics of Fluids, 34(10), 2022.
[2] Culda, L. I. RFID Technology in Production and Post Production for the Automotive Industry. Robotica & Management, 28(1), 2023.
[3] Kuş, A. Implementation of 3D Optical Scanning Technology for Automotive Applications. Sensors, 9(3), 1967-1979, 2009.
[4] O'Mahony, N., Campbell, S., Carvalho, A., Harapanahalli, S., Hernandez, G. V., Krpalkova, L., et al. Deep Learning vs. Traditional Computer Vision. In Advances in Computer Vision: Proceedings of the 2019 Computer Vision Conference (CVC), Volume 1, Springer, 2020.
[5] Jung, H., Rhee, J. Application of YOLO and ResNet in Heat Staking Process Inspection. Sustainability, 14(23), 15892, 2022.
[6] Li, Z., Tian, X., Liu, X., Liu, Y., Shi, X. A Two-Stage Industrial Defect Detection Framework Based on Improved-YOLOv5 and Optimized-Inception-ResNetv2 Models. Applied Sciences, 12(2), 834, 2022.
[7] Li, C., Li, L., Jiang, H., Weng, K., Geng, Y., Li, L., et al. YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications. arXiv preprint arXiv:2209.02976, 2022.
[8] Puttemans, S., Callemein, T., Goedemé, T. Building Robust Industrial Applicable Object Detection Models Using Transfer Learning and Single Pass Deep Learning Architectures. arXiv preprint arXiv:2007.04666, 2020.
[9] Chen, Z., He, Z., Chao, B., Guo, H. Visual Detection Application of Lightweight Convolution and Deep Residual Networks in Wood Production. Wireless Communications and Mobile Computing, 2022(1), 9465433, 2022.
[10] Lee, Y., Kim, H., Park, E., Cui, X., Kim, H. Wide-Residual-Inception Networks for Real-Time Object Detection. 2017 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2017.
[11] Wang, H., Peng, J., Zhao, Y., Fu, X. Multi-Path Deep CNNs for Fine-Grained Car Recognition. IEEE Transactions on Vehicular Technology, 69(10), 10484-10493, 2020.
[12] Huttunen, H., Yancheshmeh, F. S., Chen, K. Car Type Recognition with Deep Neural Networks. 2016 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2016.
[13] Nazemi, A., Shafiee, M. J., Azimifar, Z., Wong, A. Unsupervised Feature Learning Toward a Real-Time Vehicle Make and Model Recognition. arXiv preprint arXiv:1806.03028, 2018.
[14] Schulzrinne, H., Rao, A., Lanphier, R., Westerlund, M., Stiemerling, M. Real-Time Streaming Protocol (RTSP). RFC 2326, April 1998. [Online]. Available: https://tools.ietf.org/html/rfc2326.
[15] FFmpeg Documentation. FFmpeg, 2025. [Online]. Available: https://ffmpeg.org/ffmpeg-all.html.
[16] MathWorks. TrainingOptions Documentation. 2019. [Online]. Available: https://www.mathworks.com/help/deeplearning/ref/trainingoptions.html. Accessed: May 14, 2025.