References
- 1. Burnos, P., Gajda, J., Piwowar, P., Sroka, R., Stencel, M., Zeglen, T. (2007) Measurements of road traffic parameters using inductive loops and piezoelectric sensors.
- 2. Sun, C., Ritchie, S. G. and Tsai, K. (1998) Algorithm development for derivation of section-related measures of traffic system performance using inductive loop detectors. Transportation Research Record, 1643(1), pp. 171–180.10.3141/1643-21
- 3. Slimani, I., Zaarane, A., Hamdoun, A., Atouf, I. (2018) Traffic surveillance system for vehicle detection using discrete wavelet transform. Journal of Theoretical & Applied Information Technology, 96(17).
- 4. AL Okaishi, W., Zaarane, A., Slimani, I., Atouf, I., Benrabh, M. (2019a) Vehicular queue length measurement based on edge detection and vehicle feature extraction. Journal of Theoretical & Applied Information Technology, 97(5).
- 5. Fathy, M., Siyal, MY. (1995) Real-time image processing approach to measure traffic queue parameters. IEE Proceedings-Vision, Image and Signal Processing, 142(5), pp. 297–303.10.1049/ip-vis:19952064
- 6. Albiol, A., Albiol, A., Mossi, J. M. (2011a) Video-based traffic queue length estimation. Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on. IEEE, pp. 1928–1932.10.1109/ICCVW.2011.6130484
- 7. Chintalacheruvu, N., Muthukumar, V. (2012) Video based vehicle detection and its application in intelligent transportation systems. Journal of Transportation Technologies, 2(04), p. 305.10.4236/jtts.2012.24033
- 8. Albiol, A., Sanchis, L., Albiol, A., Mossi, J. M. (2011b) Detection of parked vehicles using spatiotemporal maps. IEEE Transactions on Intelligent Transportation Systems, 12(4), pp. 1277–1291.10.1109/TITS.2011.2156791
- 9. Rourke, A., Bell, M. (1991) Queue detection and congestion monitoring using image processing. Traffic engineering & control, 32(9).
- 10. Siyal, M. Y., Fathy, M. (1999) A neural-vision based approach to measure traffic queue parameters in real-time. Pattern Recognition Letters, 20(8), pp. 761–770.10.1016/S0167-8655(99)00040-9
- 11. Iwasaki, Y. (1997) An image processing system to measure vehicular queues and an adaptive traffic signal control by using the information of the queues. Intelligent Transportation System, ITSC’97., IEEE Conference on. IEEE, pp. 195–200.10.1109/ITSC.1997.660474
- 12. Zanin, M., Messelodi, S., Modena, C. M. (2003) An efficient vehicle queue detection system based on image processing. null. IEEE, p. 232.10.1109/ICIAP.2003.1234055
- 13. Shirazi, M. S., Morris, B. (2015) Vision-based vehicle queue analysis at junctions. Advanced Video and Signal Based Surveillance (AVSS), 2015 12th IEEE International Conference on. IEEE, pp. 1–6.10.1109/AVSS.2015.7301732
- 14. Sen-Ching, S. C., Kamath, C. (2004) Robust techniques for background subtraction in urban traffic video. Visual Communications and Image Processing. International Society for Optics and Photonics, 5308, pp. 881–893.
- 15. AL Okaishi, W., Atouf, I., Benrabh, M. (2019b) Real-Time Traffic Light Control System Based on Background Updating and Edge Detection. 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS) on. IEEE, pp. 1–5.10.1109/WITS.2019.8723752
- 16. Lowe, D. (2004) Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60, pp. 91–110.10.1023/B:VISI.0000029664.99615.94
- 17. Dalal, N., Triggs, B. (2005) Histograms of oriented gradients for human detection. IEEE computer society conference on computer vision and pattern recognition (CVPR’05), 1, pp. 886–893.10.1109/CVPR.2005.177
- 18. Tan, X., Triggs, B. (2007) Fusing Gabor and LBP feature sets for kernel-based face recognition. International workshop on analysis and modeling of faces and gestures, pp. 235–249.10.1007/978-3-540-75690-3_18
- 19. Nogueira, K., Miranda, W. O., Dos Santos, J. A. (2015) Improving spatial feature representation from aerial scenes by using convolutional networks. Graphics, Patterns and Images (SIBGRAPI), 2015 28th SIBGRAPI Conference on, IEEE, pp. 289–296.10.1109/SIBGRAPI.2015.39
- 20. Krizhevsky, A., Sutskever, I., Hinton, G. E. (2012) Imagenet classification with deep convolutional neural networks. Neural Information Processing Systems, pp. 1106–1114.
- 21. Simonyan, K., Zisserman, A. (2014) Very deep convolutional networks for large-scale image recognition,” arXiv preprint arXiv: 1409.1556.
- 22. Girshick, R., Donahue, J., Darrell, T. (2015a) Region-based convolutional networks for accurate object detection and segmentation. IEEE transactions on pattern analysis and machine intelligence, 38(1), pp. 142–158.10.1109/TPAMI.2015.243738426656583
- 23. Girshick, R. (2015b) Fast R-CNN. IEEE International Conference on Computer Vision (ICCV), pp. 1440–1448.10.1109/ICCV.2015.169
- 24. Ren, S., HE, K., Girshick, R., Sun, J. (2015) Faster R-CCN: Towards real-time object detection with region proposal networks. Advances in neural information processing systems, pp. 91–99.