RADAR OBJECT TYPE CLASSIFICATION USING KERNEL POINT CONVOLUTION LSTM NEURAL NETWORKS
DOI:
https://doi.org/10.24867/29BE26LunicKeywords:
Artifitial intelligence, Neural networks, Radar type classificationAbstract
Rad predstavlja model neuronskih mreža za klasifikaciju tipa radaskog objekta na osnovu skupa tačaka koje definišu objekat. Arhitektura koristi konvolucije na neuređenim skupovima tačaka u okviru kratkotrajno-dugotrajne memorijske ćelije da enkodira geometriju i osobine tačaka kroz vreme. Model pokazuje visoke mere performansi na skupu podataka View of Delft sa 94% tačnosti i 0.94 F1 merom na klasama pešaka, automobila i biciklista.
References
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[2] Qi, C.R., Yi, L., Su, H. and Guibas, L.J., 2017. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in neural information processing systems, 30.
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[6] Fent, F., 2020. Machine Learning-Based Radar Point Cloud Segmentation.
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[2] Qi, C.R., Yi, L., Su, H. and Guibas, L.J., 2017. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in neural information processing systems, 30.
[3] Thomas, H., Qi, C.R., Deschaud, J.E., Marcotegui, B., Goulette, F. and Guibas, L.J., 2019. Kpconv: Flexible and deformable convolution for point clouds. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 6411-6420).
[4] Palffy, A., Pool, E., Baratam, S., Kooij, J.F. and Gavrila, D.M., 2022. Multi-class road user detection with 3+ 1D radar in the View-of-Delft dataset. IEEE Robotics and Automation Letters, 7(2), pp.4961-4968.
[5] Nobis, F., Fent, F., Betz, J. and Lienkamp, M., 2021. Kernel point convolution LSTM networks for radar point cloud segmentation. Applied Sciences, 11(6), p.2599.
[6] Fent, F., 2020. Machine Learning-Based Radar Point Cloud Segmentation.
[7] Fan, H. and Yang, Y., 2019. PointRNN: Point recurrent neural network for moving point cloud processing. arXiv preprint arXiv:1910.08287.
[8] Schumann, O., Hahn, M., Dickmann, J. and Wöhler, C., 2018, July. Semantic segmentation on radar point clouds. In 2018 21st International Conference on Information Fusion (FUSION) (pp. 2179-2186). IEEE.
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Published
2024-11-05
Issue
Section
Electrotechnical and Computer Engineering
