Conditional GAN-based Remote Sensing Target Image Generation Method

[1]Tan Kun, Wang Xue, Du Peijun. Remote sensing image classification based on deep learning and semi supervised learning [J]. Chinese Journal of image graphics, 2019, 24 (11): 1823-1841 Zhang Zemiao, Huo Huan, Zhao Fengyu. Review of Object detection algorithms for deep convolutional neural networks [J]. Minicomputers, 2019, 40(09): 1825-1831.TanKunWangXueDuPeijunRemote sensing image classification based on deep learning and semi supervised learning [J]Chinese Journal of image graphics2019241118231841Zhang Zemiao, Huo Huan, Zhao Fengyu. Review of Object detection algorithms for deep convolutional neural networks [J]. Minicomputers, 2019, 40(09): 1825-1831Search in Google Scholar

[2]Liu Xiaobo, Liu Peng, Cai Zhihua, Qiao Yulin, Wang Ling, Wang min. research progress of optical remote sensing image target detection based on deep learning [J / OL]. Acta automatica Sinica: 1-13 [2019-12-23] https://doi.org/10.16383/j.aas.c190455.LiuXiaoboLiuPengCaiZhihuaQiaoYulinWangLingWangminresearch progress of optical remote sensing image target detection based on deep learning [J / OL]Acta automatica Sinica113[2019-12-23] https://doi.org/10.16383/j.aas.c190455Search in Google Scholar

[3]Chen Huiyuan, Liu Zeyu, Guo Weiwei, Zhang Zenghui, Yu Wenxian. Fast detection method of ship target in large scene remote sensing image based on cascaded convolutional neural network [J]. Acta radari Sinica, 2019, 8 (03): 413-424ChenHuiyuanLiuZeyuGuoWeiweiZhangZenghuiYuWenxianFast detection method of ship target in large scene remote sensing image based on cascaded convolutional neural network [J]Acta radari Sinica2019803413424Search in Google Scholar

[4]Yin Ya, Huang Hai, Zhang Zhixiang. Research on ship target detection technology based on optical remote sensing image [J]. Computer science, 2019, 46 (03): 82-87YinYaHuangHaiZhangZhixiangResearch on ship target detection technology based on optical remote sensing image [J]Computer science201946038287Search in Google Scholar

[5]Xu Fang. Research on key technologies for automatic detection of sea surface targets in visible remote sensing images [D]. University of Chinese Academy of Sciences (Changchun Institute of optics, precision machinery and physics, Chinese Academy of Sciences), 2018XuFangResearch on key technologies for automatic detection of sea surface targets in visible remote sensing images [D]University of Chinese Academy of Sciences (Changchun Institute of optics, precision machinery and physics, Chinese Academy of Sciences)2018Search in Google Scholar

[6]Yang Miao. Research on ship detection algorithm in port based on optical remote sensing image [D]. Xihua University, 2018YangMiaoResearch on ship detection algorithm in port based on optical remote sensing image [D]Xihua University2018Search in Google Scholar

[7]Kingma, Diederik P, Welling, Max. Auto-Encoding Variational Bayes[J].KingmaDiederik PWellingMaxAuto-Encoding Variational Bayes[J]Search in Google Scholar

[8]Kingma, Diederik P, Rezende, Danilo J, Mohamed, Shakir, and so on. Semi-Supervised Learning with Deep Generative Models[J]. Advances in Neural Information Processing Systems, 2014, 4:3581-3589.KingmaDiederik PRezendeDanilo JMohamedShakir, and so on.Semi-Supervised Learning with Deep Generative Models[J]Advances in Neural Information Processing Systems2014435813589Search in Google Scholar

[9]Bodin, Erik, Malik, Iman, Ek, Carl Henrik, and so on. Nonparametric Inference for Auto-Encoding Variational Bayes[J].BodinErikMalikImanEkCarl Henrik, and so on.Nonparametric Inference for Auto-Encoding Variational Bayes[J]Search in Google Scholar

[10]Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[C]//Advances in neural information processing systems. 2014: 2672-2680.GoodfellowIPouget-AbadieJMirzaMGenerative adversarial nets[C]Advances in neural information processing systems201426722680Search in Google Scholar

[11]Gan LAN, Shen Hongfei, Wang Yao, Zhang Yuejin. Data set enhancement method based on improved dcgan [J / OL]. Computer application: 1-11 [2020-11-10] http://kns.cnki.net/kcms/detail/51.1307.TP.20201015.1715.017.html.GanLANShenHongfeiWangYaoZhangYuejinData set enhancement method based on improved dcgan [J / OL]Computer application111[2020-11-10] http://kns.cnki.net/kcms/detail/51.1307.TP.20201015.1715.017.htmlSearch in Google Scholar

[12]Lin Zhipeng, Zeng Libo, Wu qiongshui. Cervical cell image data enhancement based on generative antagonism network [J]. Science, technology and engineering, 2020, 20 (28): 11672-11677LinZhipengZengLiboWuqiongshuiCervical cell image data enhancement based on generative antagonism network [J]Science, technology and engineering202020281167211677Search in Google Scholar

[13]Yang Lanlan, Gao Mingyu, Wang Chenning, Feng Dongjie, LV Xinrui. Research on facial expression recognition based on data enhancement [J]. Computer products and circulation, 2020 (11): 128-129YangLanlanGaoMingyuWangChenningFengDongjieLVXinruiResearch on facial expression recognition based on data enhancement [J]Computer products and circulation202011128129Search in Google Scholar

[14]Mehdi Mirza, Simon Osindero. Conditional generative adversarial nets. [DB/OL]. (2014-11-06). CoRR. abs/1411.1784MehdiMirzaSimonOsinderoConditional generative adversarial nets[DB/OL]. (2014-11-06). CoRR. abs/1411.1784Search in Google Scholar

[15]Lu Chuanwei, sun Qun, Zhao Yunpeng, sun Shijie, Ma Jingzhen, Cheng mianmianmian, Li Yuanfu. A path extraction method based on conditional generative countermeasure network [J / OL]. Journal of Wuhan University (Information Science Edition): 1-10 [2020-11-10] https://doi.org/10.13203/j.whugis20190159.LuChuanweisunQunZhaoYunpengsunShijieMaJingzhenChengmianmianmianLiYuanfuA path extraction method based on conditional generative countermeasure network [J / OL]Journal of Wuhan University (Information Science Edition)110[2020-11-10] https://doi.org/10.13203/j.whugis20190159Search in Google Scholar