| Citation: | WU Hai-bin, WEI Xi-ying, LIU Mei-hong, WANG Ai-li, LIU He, IWAHORI Yu-ji. Improved YOLOv4 for dangerous goods detection in X-ray inspection combined with atrous convolution and transfer learning[J]. Chinese Optics, 2021, 14(6): 1417-1425. doi: 10.37188/CO.2021-0078
|
| [1] |
鞠默然, 罗海波, 刘广琦, 等. 采用空间注意力机制的红外弱小目标检测网络[J]. 光学 精密工程,2021,29(4):843-853. doi: 10.37188/OPE.20212904.0843
JU M R, LUO H B, LIU G Q, et al. Infrared dim and small target detection network based on spatial attention mechanism[J]. Optics and Precision Engineering, 2021, 29(4): 843-853. (in Chinese) doi: 10.37188/OPE.20212904.0843
|
| [2] |
马立, 巩笑天, 欧阳航空. Tiny YOLOV3目标检测改进[J]. 光学 精密工程,2020,28(4):988-995.
MA L, GONG X T, OUYANG H K. Improvement of Tiny YOLOV3 target detection[J]. Optics and Precision Engineering, 2020, 28(4): 988-995. (in Chinese)
|
| [3] |
MERY D, SVEC E, ARIAS M, et al. Modern computer vision techniques for X-ray testing in baggage inspection[J]. IEEE Transactions on Systems,Man,and Cybernetics:Systems, 2017, 47(4): 682-692. doi: 10.1109/TSMC.2016.2628381
|
| [4] |
AYDIN I, KARAKOSE M, AKIN E. A new approach for baggage inspection by using deep convolutional neural networks[C]. 2018 International Conference on Artificial Intelligence and Data Processing (AIDP), IEEE, 2018: 1-6.
|
| [5] |
MORRIS T, CHIEN T, GOODMAN E. Convolutional neural networks for automatic threat detection in security X-ray images[C]. 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, 2018: 285-292.
|
| [6] |
AKCAY S, KUNDEGORSKI M E, WILLCOCKS C G, et al. Using deep convolutional neural network architectures for object classification and detection within X-ray baggage security imagery[J]. IEEE Transactions on Information Forensics and Security, 2018, 13(9): 2203-2215. doi: 10.1109/TIFS.2018.2812196
|
| [7] |
AKÇAY S, ATAPOUR-ABARGHOUEI A, BRECKON T P. Skip-GANomaly: skip connected and adversarially trained encoder-decoder anomaly detection[C]. Proceedings of 2019 International Joint Conference on Neural Networks (IJCNN), IEEE, 2019: 1-8.
|
| [8] |
GALVEZ R L, DADIOS E P, BANDALA A A, et al.. Threat object classification in X-ray images using transfer learning[C]. Proceedings of 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), IEEE, 2018: 1-5.
|
| [9] |
唐浩漾, 王燕, 张小媛, 等. 基于特征金字塔的X光机危险品检测算法[J]. 西安邮电大学学报,2020,25(2):58-63.
TANG H Y, WANG Y, ZHANG X Y, et al. Dangerous goods detection algorithm by X-ray machine based on feature pyramid[J]. Journal of Xi'an University of Posts and Telecommunications, 2020, 25(2): 58-63. (in Chinese)
|
| [10] |
张友康, 苏志刚, 张海刚, 等. X光安检图像多尺度违禁品检测[J]. 信号处理,2020,36(7):1096-1106.
ZHANG Y K, SU ZH G, ZHANG H G, et al. Multi-scale prohibited item detection in X-ray security image[J]. Journal of Signal Processing, 2020, 36(7): 1096-1106. (in Chinese)
|
| [11] |
郭守向, 张良. Yolo-C: 基于单阶段网络的X光图像违禁品检测[J]. 激光与光电子学进展,2021,58(8):0810003.
GUO SH X, ZHANG L. Yolo-C: one-stage network for prohibited items detection within X-ray images[J]. Laser &Optoelectronics Progress, 2021, 58(8): 0810003. (in Chinese)
|
| [12] |
ZHU Y, ZHANG Y T, ZHANG H G, et al. Data augmentation of X-ray images in baggage inspection based on generative adversarial networks[J]. IEEE Access, 2020, 8: 86536-86544. doi: 10.1109/ACCESS.2020.2992861
|
| [13] |
陈科峻, 张叶. 基于YOLO-v3模型压缩的卫星图像船只实时检测[J]. 液晶与显示,2020,35(11):1168-1176. doi: 10.37188/YJYXS20203511.1168
CHEN K J, ZHANG Y. Real-time ship detection in satellite images based on YOLO-v3 model compression[J]. Chinese Journal of Liquid Crystals and Displays, 2020, 35(11): 1168-1176. (in Chinese) doi: 10.37188/YJYXS20203511.1168
|
| [14] |
REDMON J, DIVVALA S, GIRSHICK R, et al.. You only look once: unified, real-time object detection[C]. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2016: 779-788.
|
| [15] |
刘杨帆, 曹立华, 李宁, 等. 基于YOLOv4的空间红外弱目标检测[J]. 液晶与显示,2021,36(4):615-623. doi: 10.37188/CJLCD.2020-0227
LIU Y F, CAO L H, LI N, et al. Detection of space infrared weak target based on YOLOv4[J]. Chinese Journal of Liquid Crystals and Displays, 2021, 36(4): 615-623. (in Chinese) doi: 10.37188/CJLCD.2020-0227
|
| [16] |
BOCHKOVSKIY A, WANG C Y, LIAO H Y M.YOLOv4: optimal speed and accuracy of object detection[J/OL]. arXiv: 2004.10934, 2020(2020-04-23). https://arxiv.org/abs/2004.10934.
|
| [17] |
MIAO C J, XIE L X, WAN F, et al.. SIXray: A large-scale security inspection X-ray benchmark for prohibited item discovery in overlapping images[C]. Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2019: 2114-2123.
|
| [18] |
REDMON J, FARHADI A.YOLOv3: an incremental improvement[J]. arXiv e-prints arXiv: 1804.02767, 2018.
|
| [19] |
ZHAO Q J, SHENG T, WANG Y T, et al. M2Det: a single-shot object detector based on multi-level feature pyramid network[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 2019, 33(1): 9259-9266.
|
| [20] |
LIU W, ANGUELOV D, ERHAN D, et al.. SSD: single shot multibox detector[C]. 14th European Conference on Computer Vision (CVPR), Springer, 2016: 21-37.
|
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