Infrared Technology, Volume. 44, Issue 11, 1161(2022)

Research on 3D Target Recognition Algorithm Based on Infrared Features

Yan XIA
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    References(8)

    [1] [1] REN S, HE K, Girshick R, et al. Faster R-CNN: Real-time target detection in regional planning Network[J]. IEEE Pair Model Analysis and Machinery Information, 2017, 39(6): 1137-1149.

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    [5] [5] Sochor J, Spa ň hel J, Herout A. Boxcars: improving fine-grained recognition of vehicles using 3-d bounding boxes in traffic surveillance[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(1): 97-108.

    [6] [6] Sochor J, Herout A, Havel J. BoxCars: 3D boxes as CNN input for improved fine-grained vehicle recognition[C]// IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016: 3006-3015.

    [7] [7] Dubská M, Herout A, Juránek R, et al. Fully automatic roadside camera calibration for traffic surveillance[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 16(3): 1162-1171.

    [8] [8] Dubská M, Herout A, Sochor J. Automatic camera calibration for traffic understanding[C]// Proceedings of the British Machine Vision Conference(BMVC), 2014: 1-12.

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    [12] [12] YAN Y, MAO Y, LI B. Second: sparsely embedded convolutional detection[J]. Sensors, 2018, 18(10): 3337/1-17.

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    XIA Yan. Research on 3D Target Recognition Algorithm Based on Infrared Features[J]. Infrared Technology, 2022, 44(11): 1161

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    Paper Information

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    Received: Apr. 12, 2022

    Accepted: --

    Published Online: Feb. 4, 2023

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