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NTIS 바로가기대한임베디드공학회논문지 = IEMEK Journal of embedded systems and applications, v.18 no.6, 2023년, pp.319 - 325
강지헌 (Duksung Women's University)
In this study, we proposed a method for hyperparameter optimization in the building and training of a deep learning model designed to process point cloud data collected by a millimeter-wave radar system. The primary aim of this study is to facilitate the deployment of a baseline model in resource-co...
C. Yu, Z. Xu, K. Yan, Y. R. Chien, S. H. Fang, H. C.?Wu, "Noninvasive Human Activity Recognition Using?Millimeter-Wave Radar," IEEE Systems Journal, Vol. 16,?No 2, pp. 3036-3047, 2022.
A. Shastri, N. Valecha, E. Bashirov, H. Trtaria, M.?Lentmaier, F. Tufvesson, M. Rossi, P. Casari, "A?Review of Millimeter Wave Device-Based Localization?and Device-Free Sensing Technologies and?Applications," IEEE Communications Surveys & Tutorials, Vol. 24, No. 3, pp. 1708-1749, 2022.
B. Liu, K. Ma, H. Fu, K. Wang, F. Meng, "IRecent?Progress of Silicon-Based Millimeter-Wave SoCs for?Short-Range Radar Imaging and Sensing," IEEE?Transactions on Circuits and Systems II: Express?Briefs, Vol. 69, No. 6, pp. 2667-2671, 2022.
Y. Rong, I. Lenz, D. W. Bliss, "Vital Signs Detection?Based on High-Resolution 3-D mmWave Radar?Imaging," 2022 IEEE International Symposium on?Phased Array Systems & Technology.
S. Lyer, L. Zhao, M. P. Mohan, J. Jimenno, M. Y. Siyal,?A. Alphones, M. F. Karim, "mm-Wave Radar-Based?Vital Signs Monitoring and Arrhythmia Detection Using?Machine Learning," Sensors, Vol. 22, No. 9, 2022.
A. D. Singh, S. S. Sandha, L. Garcia, M. Srivastava,?"RadHAR: Human Activity Recognition from Point?Clouds Generated through a Millimeter-wave Radar,"?Proceedings of the 3rd ACM Workshop on?Millimeter-wave Networks and Sensing Systems, pp.?51-56, 2019.
H. Arab, I. Ghaffari, L. Chioukh, S. O. Tatu,?StevenDufour, "A Convolutional Neural Network for?Human Motion Recognition and Classification Using a?dxMillimeter-Wave Doppler Radar," IEEE Sensors?Journal, Vol. 22, No. 5, pp. 4494-4502, 2022.
P. P. Ray, "A review on TinyML: State-of-the-art and?Prospects," Journal of King Saud University - Computer?and Information Sciences, Vol. 34, No. 4, pp. 1595-1623,?2022.
F. J. Adbu, Y. Zhang, M. Fu, Y. Li, Z. Deng,?"Application of Deep Learning on Millimeter-Wave?Radar Signals: A Review," Sensors, Vol. 21, No. 6,?2021.
T. Stadelmayer, M. Standelmayer, A. Santra, R.?Weigel, F. Lurz, "Human Activity Classification Using?mm-Wave FMCW Radar by Improved Representation?Learning," Proceedings of the 4th ACM Workshop on?Millimeter-Wave Networks and Sensing Systems, Vol.?1, No. 1, pp. 1-6, 2020.
H. Zhou, Y. Zhao, Y. Liu, S. Lu, X. An, Q. Liu,?"Multi-Sensor Data Fusion and CNN-LSTM Model for?Human Activity Recognition System," Sensors, Vol. 23,?No. 10, 2023.
X. Huang, N. Patel, K. P. Tsoi, "Application of?mmWave Radar Sensor for People Identification and?Classification," Sensors, Vol. 23, No. 8, 2023.
S. Bai, J. Z. Kolter, V. Koltun, "An Empirical?Evaluation of Generic Convolutional and Recurrent?Networks for Sequence Modeling," arXiv:1803.01271,?2018.
C. R. Qi, H. Su, K. Mo, L. J. Guibas, "PointNet: Deep?Learning on Point Sets for 3D Classification and?Segmentation," Proceedings of the IEEE Conference?on Computer Vision and Pattern Recognition, pp.?652-660, 2017.
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