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English Information

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Authors
# Name
1 Ednilza Nardi(ednilza@ime.usp.br)
2 Bruno Padilha(brunopadilha@usp.br)
3 Leonardo Kamaura(ltkamaura@alumni.usp.br)
4 João Ferreira(jef@ime.usp.br)

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Reference
# Reference
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19 Robert, Ross, Marcin, Elvis, Guillem, Andrew, and Thomas (2022). Papers with code. https://paperswithcode.com/sota/object-detection-on-coco. Acessado em 20/05/2022.
20 Santhosh, K. K., Dogra, D. P., and Roy, P. P. (2020). Anomaly detection in road traffic using visual surveillance: A survey. ACM Comput. Surv., 53(6).
21 Tan, M., Pang, R., and Le, Q. V. (2020). Efficientdet: Scalable and efficient object detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 10778–10787. IEEE.
22 Wang, T., He, X., Su, S., and Guan, Y. (2017). Efficient scene layout aware object detection for traffic surveillance. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 926–933. IEEE.
23 Zaidi, S. S. A., Ansari, M. S., Aslam, A., Kanwal, N., Asghar, M., and Lee, B. (2022). A survey of modern deep learning based object detection models. Digital Signal Processing, 126:103514.
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25 Zhou, X., Gong, W., Fu, W., and Du, F. (2017). Application of deep learning in object detection. In 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), pages 631–634. IEEE.
26 Zhuang, F., Qi, Z., Duan, K., Xi, D., Zhu, Y., Zhu, H., Xiong, H., and He, Q. (2020). A comprehensive survey on transfer learning. Proceedings of the IEEE, 109(1):43–76.