GAN-based data augmentation of prohibited item X-ray images in security inspection

Yue ZHU; Hai-gang ZHANG; Jiu-yuan AN; Jin-feng YANG

doi:10.1007/s11801-020-9116-z

[1] Akcay S, Kundegorski M E, Devereux M and Breckon Y P, Transfer Learning Using Convolutional Neural Networks for Object Classification within X-Ray Baggage Security Imagery, IEEE International Conference on Image Processing, 1057 (2016).

[2] R. Girshick, Fast R-CNN, IEEE International Conference on Computer Vision, 1440 (2015).

[3] Akcay S, Kundegorski M E, Willcocks C G and Breckon Y P, IEEE Transactions on Information Forensics and Security 13, 2203 (2018).

[4] Xu Mao-shu, Zhang Hai-gang and Yang Jin-feng, Prohibited Item Detection in Airport X-Ray Security Images via Attention Mechanism Based CNN, Chinese Conference on Pattern Recognition and Computer Vision, 429 (2018).

[5] Mery D, Svec E, Arias M, Riffo V, Saavedra J M and Banerjee S, IEEE Transactions on Systems, Man, and Cybernetics 47, 682 (2017).

[6] Miao C, Xie L, Wan F, Su C, Liu H, Jiao J anf Ye Q, SIXray: A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery, Computer Vision and Pattern Recognition, 2119 (2019).

[7] Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A and Bengio Y, Generative Adversarial Nets, the 27th International Conference on Neural Information Processing Systems, 2672 (2014).

[8] Radford A, Metz L and Chintala S, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, arXiv:1511.06434, (2015).

[9] Gulrajani I, Ahmed F, Arjovsky M, Dumoulin V and Courville A C, Improved Training of Wasserstein GANs, arXiv:1704.00028, (2017).

[10] Zhang H, Goodfellow I, Metaxas D and Odena A, Self-Attention Generative Adversarial Networks, arXiv:1805.08318, (2018).

[11] Brock A, Donahue J and Simonyan K, Large Scale GAN Training for High Fidelity Natural Image Synthesis, arXiv: 1809.11096, (2018).

[12] Antoniou A, Amos S and Harrison E, Data Augmentation Generative Adversarial Networks, arXiv: 1711.04340, (2017).

[13] Frid-Adar M, Klang E, Amitai M, Goldberger J and Greenspan H, Synthetic Data Augmentation Using GAN for Improved Liver Lesion Classification, 15th International Symposium on Biomedical Imaging, 289 (2018).

[14] Zhao Z H, Zhang H G and Yang J F, A GAN-Based Image Generation Method for X-Ray Security Prohibited Items. Pattern Recognition and Computer Vision, 420 (2018).

[15] Heuse H, Ramsauer H, Unterthiner T, Nessler B and Hochreiter S, GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium, Neural Information Processing Systems, 6629 (2017).

[16] K Shmelkov, C Schmid and K Alahari, How Good is My GAN? European Conference on Computer Vision, 213 (2018).

[17] Wang X, Girshick R, Gupta A and He Kai-ming, Non-local Neural Networks, IEEE Conference on Computer Vision and Pattern Recognition, 7794 (2018).

[18] Lim J H and Ye J C, Geometric GAN, arXiv: 1705.02894, (2017).

[19] Salimans T, Goodfellow I, Zaremba W, Cheung V, Radford A and Chen X, Improved Techniques for Training GANs, Neural Information Processing Systems, 2234 (2016).