과제정보
본 연구는 2023년 과학기술정보통신부 및 정보통신기획평가원의 SW중심대학사업의 연구결과로 수행되었음(2022-0-01068)
참고문헌
- Boukary, N. A. (2016) "A comparison of time series forecasting learning algorithms on the task of predicting event timing", Master of Applied Science thesis, Royal Military College of Canada.
- Brostrom, M. "YOLO Tracking", Available at https://github.com/mikel-brostrom/yolo_tracking (Accessed July 14. 2023).
- Chae, H., Kwak, K., Lee, D., and Kim, E. (2023) "An paproach using LSTM model to forecasting customer congestion based on indoor human tracking in video streaming", KSS Spring Conference, June 2023.
- Choi, G.W., Ahn, W.S., Yang, J.Y., and Kim, D.H. (2021) "Congestion measurement and visualization system for Han River Park", Proceedings of the Korean Information Technology Society Conference, 559-564.
- Dey, R. and Salem, F. M. (2017) "Gate-variants of gated recurrent unit (GRU) neural networks", 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), Boston, MA, USA, 1597-1600.
- Du, Y., Zhao, Z., Song, Y., Zhao, Y., Su, F., Gong, T., and Meng, H. (2023) "StrongSORT: make DeepSORT great again" IEEE Transactions on Multimedia, Early Access. doi: 10.1109/TMM.2023.3240881 (Accessed July 18. 2023).
- Iqbal, M., Al-Obeidat, F., Razzaq, S., Anwar, S., Tubaishat, A., Khan, M. S. and Shah, B. (2021) "COVID-19 patient count prediction using LSTM", IEEE Trans. on Computational Social Systems, 8 (4), 974-981.
- Ito, K. and Xiong, K. (2000) "Gaussian filters for nonlinear filtering problems", IEEE Trans. on Automatic Control, 45(5), 910-927. https://doi.org/10.1109/9.855552
- Kim, B.S. (2020) "Optimization study of intelligent CCTV system for visitor detection", Master's thesis, Kangwon National University Graduate School, Gangneung.
- Kim, D.H., Hwang, K.Y., and Yoon, Y. (2019) "Prediction of traffic congestion by Deep Neural Networks (DNN) and multidimensional context information for Seoul city road links", Journal of the Korean ITS Society, 18(4), 44-57. https://doi.org/10.12815/kits.2019.18.4.44
- Kim, G.W., No, G.S., Kim, D.W. and Lee, J.Y. (2015) "Exploratory study on improving subway congestion through big data fusion", Journal of Digital Convergence, 13(2), 35-42. https://doi.org/10.14400/JDC.2015.13.2.35
- Kim, J.S. (2016) "prediction and recommendation system for subway congestion using big data analysis", Journal of Digital Convergence, 14(11), 289-295. https://doi.org/10.14400/JDC.2016.14.11.289
- Kim, J.W., Lee, T.W., Kim, D.Y., and Lee, J.H. (2019) "Implementation of real-time people counting and congestion detection system based on ultrasonic sensor", Proceedings of the Korean Institute of Communications and Information Sciences Conference, 308-309.
- Kim, M.J., Go, S.Y., and Jeong, N.H. (2021) "Case study of Jeju tourism organization's real-time tourism site congestion analysis service", Journal of Information Technology Services, 20(5), 29-41.
- Kim, S.H., Park, H.J., Oh, J.E., and Lee, K.Y. (2021) "Development of cafe congestion information application using deep Learning-based object detection technology", Proceedings of the Korean Information Science Society Conference, 1342-1344.
- Koutnik, J., Greff, K., Gomez, and F., Schmidhuber, J. (2014) "A Clockwork RNN", arXiv preprint arXiv:1402.3511. Available at https://doi.org/10.48550/arXiv.1402.3511 (Accessed July 18. 2023).
- Kwon, S.H., Lee, S.C., and Kim, H.S. (2021) "Development of congestion estimation program in spatial environment using IEEE 802.11 proberequest", Proceedings of the Korean Computer Information Society Academic Conference, 29(2), 257-260.
- Lee, H.S., Nam, B.C., and Seon, C.N. (2020) "Deep learning LSTM framework for urban traffic flow and fine dust prediction", Journal of Korean Information Science Society, 47(3), 292-297.
- Lee, T.W., Kim, J.W., Kim, D.Y., and Lee, J.H. (2018) "Personnel counting algorithm for emergency exits based on multiple ultrasonic sensors" Proceedings of the Korean Communications Society Conference, 299-300.
- Park, Y. (2023) "Concise logarithmic loss function for robust training of anomaly detection model", arXiv preprint arXiv: 2201.05748v2. Available at https://doi.org/10.48550/arXiv.2201.05748 (Accessed July 17. 2023).
- poiuyreq0 (2023) "KOKO", Available at https://github.com/poiuyreq0/KOKO(Accessed July 14. 2023).
- Qolomany, B., Al-Fuqaha, A., Benhaddou, D. and Gupta, A. (2017) "Role of deep LSTM neural networks and Wi-Fi networks in support of occupancy prediction in Smart Buildings", 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3d Systems (HPCC/SmartCity/DSS), 50-57, doi: 10.1109/HPCC-SmartCity-DSS.2017.7 (Accessed July 16, 2023).
- Sojasingarayar, A. (2020) "Seq2Seq AI Chatbot with Attention Mechanism", arXiv preprint arXiv: 2006.02767. Available at https://doi.org/10.48550/arXiv.2006.02767 (Accessed July 16. 2023).
- Sultana, F., Sufian, A., Dutta, P. (2019) "A review of object detection models based on convolutional neural network", arXiv preprint arXiv: 1905.01614. Available at https://doi.org/10.48550/arXiv.1905.01614 (Accessed July 18. 2023).
- Ultralytics "YOLO" Available at https://github.com/ultralytics/ultralytics/tree/15b3b0365ab2f12993a58985f3cb7f2137409a0c (Accessed July 14. 2023).