激光与光电子学进展, 2019, 56 (7): 071102, 网络出版: 2019-07-30   

基于深度神经网络的迷彩目标发现仿真学习方法 下载: 1152次

Simulation Learning Method for Discovery of Camouflage Targets Based on Deep Neural Networks
作者单位
1 江南大学数字媒体学院, 江苏 无锡 214122
2 江苏省媒体设计与软件技术重点实验室, 江苏 无锡 214122
3 近地面探测与感知技术国防科技重点实验室, 江苏 无锡 214035
引用该论文

卓刘, 陈晓琪, 谢振平, 蒋晓军, 毕道鹍. 基于深度神经网络的迷彩目标发现仿真学习方法[J]. 激光与光电子学进展, 2019, 56(7): 071102.

Liu Zhuo, Xiaoqi Chen, Zhenping Xie, Xiaojun Jiang, Daokun Bi. Simulation Learning Method for Discovery of Camouflage Targets Based on Deep Neural Networks[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071102.

参考文献

[1] 张海瑞, 李彦彬, 邢瑞康, 等. 基于集对分析的防空导弹装备红外伪装能力评估[J]. 激光与光电子学进展, 2018, 55(7): 070402.

    Zhang H R, Li Y B, Xing R K, et al. Evaluation of air defense missile infrared camouflage capability based on set pair analysis[J]. Laser & Optoelectronics Progress, 2018, 55(7): 070402.

[2] 郭彤, 华文深, 刘恂, 等. 一种基于高光谱的光学伪装效果综合评价方法[J]. 激光与光电子学进展, 2016, 53(10): 101002.

    Guo T, Hua W S, Liu X, et al. Comprehensive evaluation of optical camouflage effect based on hyperspectra[J]. Laser & Optoelectronics Progress, 2016, 53(10): 101002.

[3] 白雪琼, 廖宁放, 黄浩, 等. 基于色差和光谱特性的海面船只隐身效果评估[J]. 激光与光电子学进展, 2018, 55(9): 093301.

    Bai X Q, Liao N F, Huang H, et al. Evaluation of ship camouflage effect on sea based on color difference and spectral characteristics[J]. Laser & Optoelectronics Progress, 2018, 55(9): 093301.

[4] 蔡伟, 伍樊成, 杨志勇, 等. 磁光调制技术与应用研究[J]. 激光与光电子学进展, 2015, 52(6): 060003.

    Cai W, Wu F C, Yang Z Y, et al. Research on magneto-optic modulation technology and application[J]. Laser & Optoelectronics Progress, 2015, 52(6): 060003.

[5] 王田, 牛明生, 步苗苗, 等. 可调光程的差分偏振成像系统及其特性研究[J]. 光学学报, 2017, 37(7): 0711001.

    Wang T, Niu M S, Bu M M, et al. Polarization-difference imaging system with adjustable optical path and its characteristics[J]. Acta Optica Sinica, 2017, 37(7): 0711001.

[6] 陶菲, 宋茂新, 洪津, 等. 基于离轴三反的同时全偏振成像仪的偏振定标方法[J]. 光学学报, 2018, 38(9): 0912005.

    Tao F, Song M X, Hong J, et al. Polarization calibration method for simultaneous imaging polarimeter based on off-axis three-mirror[J]. Acta Optica Sinica, 2018, 38(9): 0912005.

[7] 王小龙, 王峰, 刘晓, 等. 荒漠背景下典型伪装目标的高光谱偏振特性[J]. 激光与光电子学进展, 2018, 55(5): 051101.

    Wang X L, Wang F, Liu X, et al. Hyperspectral polarization characteristics of typical camouflage target under desert background[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051101.

[8] 崔宝生, 薛士强, 姬艳军, 等. 图像特征的伪装效果评估技术[J]. 红外与激光工程, 2010, 39(6): 1178-1183.

    Cui B S, Xue S Q, Ji Y J, et al. Camouflage effectiveness evaluation based on image feature[J]. Infrared and Laser Engineering, 2010, 39(6): 1178-1183.

[9] 许卫东, 吕绪良, 陈兵, 等. 一种基于纹理分析的伪装器材效果评价模型[J]. 兵工学报, 2002, 23(3): 329-331.

    Xu W D, Lü X L, Chen B, et al. A model based on texture analysis for the performance evaluation of camouflage screen equipment[J]. Acta Armamentarii, 2002, 23(3): 329-331.

[10] 林伟, 陈玉华, 王吉远, 等. 基于图像特征与心理感知量的伪装效果评价方法[J]. 兵工学报, 2013, 34(4): 412-417.

    Lin W, Chen Y H, Wang J Y, et al. Camouflage assessment method based on image features and psychological perception quantity[J]. Acta Armamentarii, 2013, 34(4): 412-417.

[11] 王鹏烨, 赵德辉, 李明锋. 基于图像修复技术的目标可见光伪装效果评价[J]. 激光与光电子学进展, 2018, 55(3): 031011.

    Wang P Y, Zhao D H, Li M F. Optical camouflage effect assessment based on digital image inpainting technology[J]. Laser & Optoelectronics Progress, 2018, 55(3): 031011.

[12] 张荣, 李伟平, 莫同. 深度学习研究综述[J]. 信息与控制, 2018, 47(4): 385-397, 410.

    Zhang R, Li W P, Mo T. Review of deep learning[J]. Information and Control, 2018, 47(4): 385-397, 410.

[13] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 2017, 60(6): 84-90.

[14] He KM, Zhang XY, Ren SQ, et al. Deep residual learning for image recognition[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2016: 770- 778.

[15] HuangG, LiuZ, Maaten L V D, et al. Densely connected convolutional networks[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2017: 2261- 2269.

[16] 辛宇, 杨静, 谢志强. 基于随机游走的语义重叠社区发现算法[J]. 计算机研究与发展, 2015, 52(2): 499-511.

    Xin Y, Yang J, Xie Z Q. A semantic overlapping community detecting algorithm in social networks based on random walk[J]. Journal of Computer Research and Development, 2015, 52(2): 499-511.

[17] 王勇, 唐靖, 饶勤菲, 等. 高效率的K-means最佳聚类数确定算法[J]. 计算机应用, 2014, 34(5): 1331-1335.

    Wang Y, Tang J, Rao Q F, et al. High efficient K-means algorithm for determining optimal number of clusters[J]. Journal of Computer Applications, 2014, 34(5): 1331-1335.

[18] 安喆, 徐熙平, 杨进华, 等. 结合图像语义分割的增强现实型平视显示系统设计与研究[J]. 光学学报, 2018, 38(7): 0710004.

    An Z, Xu X P, Yang J H, et al. Design of augmented reality head-up display system based on image semantic segmentation[J]. Acta Optica Sinica, 2018, 38(7): 0710004.

[19] 李素梅, 雷国庆, 范如. 基于双通道卷积神经网络的深度图超分辨研究[J]. 光学学报, 2018, 38(10): 1010002.

    Li S M, Lei G Q, Fan R. Depth map super-resolution based on two-channel convolutional neural network[J]. Acta Optica Sinica, 2018, 38(10): 1010002.

[20] 孙汉卿, 庞彦伟. 一种自学习不确定度的神经网络架构[J]. 光学学报, 2018, 38(6): 0620002.

    Sun H Q, Pang Y W. An neural network framework of self-learning uncertainty[J]. Acta Optica Sinica, 2018, 38(6): 0620002.

[21] LongJ, ShelhamerE, DarrellT. Fully convolutional networks for semantic segmentation[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2015: 3431- 3440.

[22] IsolaP, Zhu JY, Zhou TH, et al. Image-to-image translation with conditional adversarial networks[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2017: 5967- 5976.

[23] Goodfellow IJ, Pouget-AbadieJ, MirzaM, et al. Generative adversarial nets[C]∥Advances in Neural Information Processing Systems, 2014: 2672- 2680.

卓刘, 陈晓琪, 谢振平, 蒋晓军, 毕道鹍. 基于深度神经网络的迷彩目标发现仿真学习方法[J]. 激光与光电子学进展, 2019, 56(7): 071102. Liu Zhuo, Xiaoqi Chen, Zhenping Xie, Xiaojun Jiang, Daokun Bi. Simulation Learning Method for Discovery of Camouflage Targets Based on Deep Neural Networks[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071102.

本文已被 2 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!