TiAM-GAN: Titanium Alloy Microstructure Image Generation Network

Author:

Zhang Zhixuan,Jin Fusheng,Gong Haichao,Fan Qunbo

Publisher

Springer Nature Singapore

Reference16 articles.

1. Brock, A., Donahue, J., Simonyan, K.: Large scale GAN training for high fidelity natural image synthesis. arXiv preprint arXiv:1809.11096 (2018)

2. Chirico, C., Romero, A.V., Gordo, E., Tsipas, S.: Improvement of wear resistance of low-cost powder metallurgy $$\beta $$-titanium alloys for biomedical applications. Surf. Coat. Technol. 434, 128207 (2022)

3. Ding, X., Wang, Y., Xu, Z., Welch, W.J., Wang, Z.J.: CcGAN: continuous conditional generative adversarial networks for image generation. In: International Conference on Learning Representations (2020)

4. Fu, Y.Y., Song, Y.Q., Hui, S.X.: Research and application of typical aerospace titanium alloys. Chin. J. Met. 30, 850–856 (2006)

5. Goodfellow, I., et al.: Generative adversarial networks. Commun. ACM 63(11), 139–144 (2020)

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