• Laser & Optoelectronics Progress
  • Vol. 59, Issue 4, 0410017 (2022)
Jingqian Qiao and Liang Zhang*
Author Affiliations
  • College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
  • show less
    DOI: 10.3788/LOP202259.0410017 Cite this Article Set citation alerts
    Jingqian Qiao, Liang Zhang. X-Ray Object Detection Based on Pyramid Convolution and Strip Pooling[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410017 Copy Citation Text show less
    References

    [1] Zhou B, Li R X, Shang Z H et al. Object detection algorithm based on improved Faster R-CNN[J]. Laser & Optoelectronics Progress, 57, 101009(2020).

    [2] Guo R H, Zhang L, Yang Y et al. X-ray image controlled knife detection and recognition based on improved SSD[J]. Laser & Optoelectronics Progress, 58, 0404001(2021).

    [3] Hosoya Y, Suganuma M, Okatani T. Analysis and a solution of momentarily missed detection for anchor-based object detectors[C], 1399-1407(2020).

    [4] Hosang J, Benenson R, Schiele B. Learning non-maximum suppression[C], 6469-6477(2017).

    [5] Duta I C, Liu L, Zhu F et al. Pyramidal convolution: rethinking convolutional neural networks for visual recognition[EB/OL]. https://arxiv.org/abs/2006.11538

    [6] Hou Q B, Zhang L, Cheng M M et al. Strip pooling: rethinking spatial pooling for scene parsing[C], 4002-4011(2020).

    [7] Rezatofighi H, Tsoi N, Gwak J et al. Generalized intersection over union: a metric and a loss for bounding box regression[C], 658-666(2019).

    [8] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

    [9] Redmon J, Farhadi A. YOLOv3: an incremental improvement[EB/OL]. https://arxiv.org/abs/1804.02767

    [10] Womg A, Shafiee M J, Li F et al. Tiny SSD: a tiny single-shot detection deep convolutional neural network for real-time embedded object detection[C], 95-101(2018).

    [11] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 318-327(2020).

    [12] Law H, Deng J. CornerNet: detecting objects as paired keypoints[J]. International Journal of Computer Vision, 128, 642-656(2020).

    [13] Zhou X Y, Zhuo J C, Krähenbühl P. Bottom-up object detection by grouping extreme and center points[C], 850-859(2019).

    [14] Zhou X Y, Wang D Q, Krähenbühl P. Objects as points[EB/OL]. https://arxiv.org/abs/1904.07850

    [15] Luo W J, Li Y J, Urtasun R et al. Understanding the effective receptive field in deep convolutional neural networks[EB/OL]. https: //arxiv.org/abs/1701.04128

    [16] Li Y H, Chen Y T, Wang N Y et al. Scale-aware trident networks for object detection[C], 6053-6062(2019).

    [17] Perreault H, Bilodeau G A, Saunier N et al. SpotNet: self-attention multi-task network for object detection[C], 230-237(2020).

    [18] Wang X L, Girshick R, Gupta A et al. Non-local neural networks[C], 7794-7803(2018).

    [19] Wang Z Y, Ji S W. Smoothed dilated convolutions for improved dense prediction[C], 2486-2495(2018).

    [20] Zhao H, Gallo O, Frosio I et al. Loss functions for image restoration with neural networks[J]. IEEE Transactions on Computational Imaging, 3, 47-57(2017).

    [21] Guo S X, Zhang L. Yolo-C: one-stage network for prohibited items detection within X-ray images[J]. Laser & Optoelectronics Progress, 58, 0810003(2021).

    Jingqian Qiao, Liang Zhang. X-Ray Object Detection Based on Pyramid Convolution and Strip Pooling[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410017
    Download Citation