[1] J LATGER, T CATHALA, N DOUCHIN et al. Simulation of active and passive infrared images using the SE-WORKBENCH, 6543, 11-25(2007).
[2] K JOHNSON, A CURRAN, D LESS et al. MuSES: a new heat and signature management design tool for virtual prototyping(1998).
[3] J R SCHOTT, S D BROWN, R V RAQUEÑO et al. An advanced synthetic image generation model and its application to multi/hyperspectral algorithm development. Canadian Journal of Remote Sensing, 25, 99-111(1999).
[4] 杨艳春, 高晓宇, 党建武, 等. 基于WEMD和生成对抗网络重建的红外与可见光图像融合[J]. 光学 精密工程, 2022, 30(3): 320-330. doi: 10.37188/OPE.20223003.0320YANGY C, GAOX Y, DANGJ W, et al. Infrared and visible image fusion based on WEMD and generative adversarial network reconstruction[J]. Opt. Precision Eng., 2022, 30(3): 320-330.(in Chinese). doi: 10.37188/OPE.20223003.0320
[5] 杨植凯, 卜乐平, 王腾, 等. 基于循环一致性对抗网络的室内火焰图像场景迁移[J]. 光学 精密工程, 2020, 28(3): 745-758. doi: 10.3788/ope.20202803.0745YANGZ K, BUL P, WANGT, et al. Scenemigration of indoor flame image based on Cycle-Consistent adversarial networks[J]. Opt. Precision Eng., 2020, 28(3): 745-758.(in Chinese). doi: 10.3788/ope.20202803.0745
[6] 徐哲, 耿杰, 蒋雯, 等. 联合训练生成对抗网络的半监督分类方法[J]. 光学 精密工程, 2021, 29(5): 1127-1135. doi: 10.37188/OPE.20212905.1127XUZ, GENGJ, JIANGW, et al. Co-training generative adversarial networks for semi-supervised classification method[J]. Opt. Precision Eng., 2021, 29(5): 1127-1135.(in Chinese). doi: 10.37188/OPE.20212905.1127
[7] P ISOLA, J Y ZHU, T H ZHOU et al. Image-to-image translation with conditional adversarial networks, 5967-5976(21).
[8] J Y ZHU, T PARK, P ISOLA et al. Unpaired image-to-image translation using cycle-consistent adversarial networks, 2242-2251(22).
[9] T KIM, H KIM et al. Learning to discover cross-domain relations with generative adversarial networks, 1857-1865(2017).
[10] Z L YI, H ZHANG, P TAN et al. DualGAN: unsupervised dual learning for image-to-image translation, 2868-2876(22).
[11] T CHEN, S KORNBLITH, M NOROUZI et al. A simple framework for contrastive learning of visual representations, 1597-1607(2020).
[13] F CHOLLET. Xception: deep learning with depthwise separable convolutions, 1800-1807(21).
[14] M GUTMANN, A HYVÄRINEN. Noise-contrastive estimation: a new estimation principle for unnormalized statistical models, 297-304(2010).
[16] Z WANG, A C BOVIK, H R SHEIKH et al. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13, 600-612(2004).
[17] Z P CHE, S PURUSHOTHAM, K CHO et al. Recurrent neural networks for multivariate time series with missing values. Scientific Reports, 8, 6085(2018).
[19] H Y CHANG, Z X WANG, Y Y CHUANG.