과제정보
이 연구는 2022년도 극동대학교 교내연구비 지원에 의하여 수행된 것임(No. FEU2022R05).
참고문헌
- Ibrahim, S. W., "A comprehensive review on intelligent surveillance systems," Communications in science and technology, Vol. 1, No. 1, 2016.
- Kim, I. S., Choi, H. S., Yi, K. M., Choi, J. Y., & Kong, S. G., "Intelligent visual surveillance-a survey," International Journal of Control, Automation and Systems, Vol. 8, No. 5, pp. 926-939, 2010. https://doi.org/10.1007/s12555-010-0501-4
- Joshi, K. A., Thakore, D. G., "A survey on moving object detection and tracking in video surveillance system," International Journal of Soft Computing and Engineering, Vol. 2, No. 3, pp. 44-48, 2012.
- Elharrouss, O., Almaadeed, N., Al-Maadeed, S., "A review of video surveillance systems," Journal of Visual Communication and Image Representation, Vol. 77, (3),103116, May 2021.
- Adrian, A. I., Ismet, P., Petru, P., "An overview of intelligent surveillance systems development," 2018 International Symposium on Electronics and Telecommunications (ISETC), pp.1-6, Timisoara, Romania, Nov. 2018.
- Haghighat, A. K., Ravichandra-Mouli, V., Chakraborty, P., Esfandiari, Y., Arabi, S., & Sharma, A., "Applications of deep learning in intelligent transportation systems," Journal of Big Data Analytics in Transportation 2020, Vol. 2, No. 11, pp. 115-145, Aug. 2020. https://doi.org/10.1007/s42421-020-00020-1
- Sreenu, G., Durai, S., "Intelligent video surveillance: a review through deep learning techniques for crowd analysis," Journal of Big Data, 6(1), pp.1-27, 2019. https://doi.org/10.1186/s40537-019-0212-5
- Girshick, R., Donahue, J., Darrell, T., Malik, J., "Rich feature hierarchies for accurate object detection and semantic segmentation," Proceedings of the IEEE conference on computer vision and pattern recognition, pp.580-587, Columbus, USA, Sep. 2014.
- Girshick, R., "Fast r-cnn," Proceedings of the IEEE international conference on computer vision, pp. 1440-1448, Santiago, Chile, Dec. 2015.
- Ren, S., He, K., Girshick, R., Sun, J., "Faster r-cnn: Towards real-time object detection with region proposal networks," Advances in neural information processing systems, 28, pp.1-9, 2015.
- Redmon, J., Divvala, S., Girshick, R., Farhadi, A., "You only look once: Unified, real-time object detection," Proceedings of the IEEE conference on computer vision and pattern recognition, pp.779-788, Jun. 2016.
- Redmon, J., Farhadi, A., "YOLO9000: better, faster, stronger," Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 7263-7271, Jul. 2017.
- He, K., Zhang, X., Ren, S., Sun, J., "Spatial pyramid pooling in deep convolutional networks for visual recognition," IEEE transactions on pattern analysis and machine intelligence, 37, pp1904-1916, 2015. https://doi.org/10.1109/TPAMI.2015.2389824
- Gidaris, S., Komodakis, N., "Object detection via a multi-region and semantic segmentation-aware cnn model," Proceedings of the IEEE international conference on computer vision, pp.1134-1142, May 2015.
- O'Byrne, M., Sugrue, M., Kokaram, A., "Impact of Video Compression on the Performance of Object Detection Systems for Surveillance Applications," 2022 18th IEEE International Conference on Advanced Video and Signal Based Surveillance(AVSS), pp. 1-8, Madrid, Spain, Nov. 2022.
- Katsamenis, I., Karolou, E. E., Davradou, A., Protopapadakis, E., Doulamis, A., Doulamis, N., Kalogeras, D., "TraCon: A novel dataset for real-time traffic cones detection using deep learning," Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022), pp. 382-391, 2022.
- Li, C., et al., "YOLOv6: A single-stage object detection framework for industrial applications," arXiv:2209.02976, 2022.