[1] 朱明明, 许悦雷, 马时平, 等. 改进区域卷积神经网络的机场检测方法[J]. 光学学报, 2018, 38(7): 0728001-1-0728001-6. ZHU M M, XU Y L, MA S P, et al. Airport detection method with improved region-based convolutional neural network[J]. Acta Optica Sinica, 2018, 38(7): 0728001-1-0728001-6.(in Chinese) [2] 潘治鸿, 窦浩, 刘迪,等. 基于直线和区域显著性融合机制的机场检测[J]. 计算机工程与应用, 2018,54(8):154-159,171. PAN Z H, DOU H, LIU D, et al. Airport detection based on straight line and regional saliency fusion mechanism [J]. Compu- ter Engineering and Applications, 2018,54(8):154-159,171.(in Chinese) [3] 艾淑芳, 闫钧华, 李大雷, 等. 遥感图像中的机场跑道检测算法[J]. 电光与控制, 2017,24(2): 43-46. AI S F, YAN J H, LI D L, et al. An algorithm for detecting the airport runway in remote sensing image[J]. Electronics Optics & Control, 2017,24(2): 43-46. (in Chinese) [4] 梁杰, 李磊, 周红丽. 基于改进SSD的舰船目标精细化检测方法[J]. 导航定位与授时, 2019,6(5):43-51. LIANG J, LI L, ZHOU H L. A ship target refinement detection method based on improved SSD[J]. Navigation Positioning and Timing, 2019,6(5):43-51. (in Chinese) [5] 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 & Machine Intelligence,2017, 39(6): 1137-1149. [6] DAI J, LI Y, HE K, et al. R-FCN: object detection via region-based fully convolutional networks[C]∥ Proceedings of Annual Conference on Neural Information Processing Systems. Barcelona, Spain: NIPS Foundation, 2016:208-217. [7] CAI Z, VASCONCELOS N. Cascade R-CNN: delving into high quality object detection[C]∥ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City, UT, US: IEEE, 2018:673-682. [8] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, real-time object detection[C]∥ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Boston, MA, US: IEEE, 2015: 779-788. [9] LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multiBox detector[C]∥ Proceedings of European Conference on Computer Vision. Amsterdam, the Netherlands: the University of Amsterdam, 2016: 21-37. [10] LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 42(2):318-327. [11] LAW H, DENG J. CornerNet: detecting objects as paired keypoints[J]. International Journal of Computer Vision, 2020, 128(3): 642-656. [12] ZHANG P, NIU X, DOU Y, et al. Airport detection from remote sensing images using transferable convolutional neural networks[C]∥Proceedings of International Joint Conference on Neural Networks. Vancouver, Canada: International Neural Network Society, 2016: 2590-2595. [13] 辛鹏, 许悦雷, 马时平, 等. 区域提取网络结合自适应池化网络的机场检测[J]. 西安电子科技大学学报, 2018, 45(3): 108-114. XIN P, XU Y L, MA S P, et al. Airport detection based on regional extraction network combined with adaptive pooling network[J]. Journal of Xidian University, 2018, 45(3): 108-114.(in Chinese) [14] 袁雷, 程岳, 牛文生, 等. 基于深度学习的跑道前视红外图像轮廓线提取[J]. 电讯技术, 2019, 59(2):59-64. YUAN L, CHENG Y, NIU W S, et al. Outline extraction of runway forward-looking infrared image based on deep learning [J]. Telecommunications Technology, 2019, 59(2): 59-64. (in Chinese) [15] REDMON J, FAEHADI A. YOLO9000: better, faster, stronger[C]∥ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, HI, US : IEEE, 2017: 6517-6525. [16] REDMON J, FAEHADI A. YOLOv3: an incremental improvement: arXiv: 1804.02767 [R/OL]. (2018-04-08)[2019-09-04]. https:∥arxiv.org/pdf/1804.02767.pdf. [17] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]∥ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, NV, US: IEEE, 2016: 556-567. [18] LIN T Y, DOLLAR P, GIRSHICK R, et al. Feature pyramid networks for object detection[C]∥ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Hawaii, HI, US: IEEE, 2017:936-944. [19] 梁杰, 李磊, 任君, 等. 基于深度学习的红外图像遮挡干扰检测方法[J].兵工学报, 2019, 40(7):1401-1410. LIANG J, LI L, REN J, et al. A method for detecting the occlusion interference in infrared image based on deep learning[J]. Acta Armamentarii, 2019, 40(7): 1401-1410.(in Chinese) [20] LIU Z, JIAN G L, ZHI Q S, et al. Learning efficient convolutional networks through network slimming[C]∥ Proceedings of IEEE International Conference on Computer Vision. Venice, Italy: IEEE, 2017:298-308. [21] HINTON G, VINVALS O, DEAN J. Distilling the knowledge in a neural network[J]. Computer Science, 2015, 14(7):38-39.
第41卷第10期2020 年10月 兵工学报ACTA ARMAMENTARII Vol.41No.10Oct. 2020
|