[1] F Wu, Z Q Zhou, B Wang, et al. Inshore ship detection based on convolutional neural network in optical satellite images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 4005-4015(2018).
[2] Z Y Zhang, S H Jiao. Infrared ship target detection method based on multiple feature fusion. Infrared and Laser Engineering, 44, 29-34(2015).
[3] Sun C H, Shrivastava A, Singh S M, et al. Revisiting unreasonable effectiveness of data in deep learning era[C] IEEE International Conference on Computer Vision (ICCV), 2017: 843852.
[4] W P Li, X G Yang, C X Li, et al. An improved semi-supervised transfer learning method for infrared object detection neural network. Infrared and Laser Engineering, 50, 20200511(2021).
[5] C Shorten, T M Khoshgoftaar. A survey on image data augmentation for deep learning. Journal of Big Data, 6, 60-72(2019).
[6] Yang X G, Chen S W, Xi J X. Heterogeneous Scene Matching Guidance Technology f Aircraft[M]. Beijing: Science Press, 2016. (in Chinese)
[7] Deng J, Dong W, Socher R, et al. Image: A largescale hierarchical image database[C]IEEE Conference on Computer Vision & Pattern Recognition (CVPR), 2009: 563584.
[8] F X Lu, X Chen, G L Chen, et al. Dim and small target detection based on background adaptive multi-feature fusion. Infrared and Laser Engineering, 48, 0326002(2019).
[9] Huang S W, Lin C T, Chen S P, et al. AugGAN: Cross domain adaptation with GANbased data augmentation[C]European Conference on Computer Vision (ECCV), 2018: 731744.
[10] D Shen, G Wu, H I Suk. Deep learning in medical image analysis. Annual Review of Biomedical Engineering, 19, 221-248(2017).
[11] X M Yu, S Hong, J X Yu, et al. Research on a ship target data augmentation method of visible remote sensing image. Chinese Journal of Scientific Instrument, 41, 261-269(2020).
[12] Cubuk E D, Zoph B, Mané D, et al. Auto augment: Learning augmentation strategies from data[C]Conference on Computer Vision Pattern Recognition (CVPR), 2019: 113123.
[13] N Dawar, S Ostadabbas, N Kehtanavaz. Data augmentation in deep learning-based fusion of depth and inertial sensing for action recognition. IEEE Sensors Letters, 3, 1-4(2019).
[14] Shaham T R, Dekel T, Michaeli T. SinGAN: Learning a generative model from a single natural image[C]International Conference on Computer Vision (ICCV), 2019: 45694579.
[15] S Y Li, G Y Fu, Z M Cui, et al. Data augmentation in SAR images based on multi-scale GAN. Laser & Optoelectronics Progress, 57, 175-185(2020).
[16] Li C, Wan M. Precomputed realtime texture synthesis with Markovian generative adversarial wks[C]European Conference on Computer Vision (ECCV), 2016. : 702716.
[17] X G Yang, F Cao, X X Huang, et al. Research on preparation method of reference image in scene matching simulation. Journal of System Simulation, 22, 850-852(2010).
[18] GulrajaniI I, Ahmed F, Arjovsky M, et al. Improved training of Wasserstein GAN[EBOL]. [20200127].https:arxiv.gabs1704.00028.