Open Access
| Issue |
ITM Web Conf.
Volume 78, 2025
International Conference on Computer Science and Electronic Information Technology (CSEIT 2025)
|
|
|---|---|---|
| Article Number | 04013 | |
| Number of page(s) | 10 | |
| Section | Foundations and Frontiers in Multimodal AI, Large Models, and Generative Technologies | |
| DOI | https://doi.org/10.1051/itmconf/20257804013 | |
| Published online | 08 September 2025 | |
- C. Shorten and T. M. Khoshgoftaar, “A survey on image data augmentation for deep learning,” J. Big Data, vol. 6, no. 1, pp. 1–48, 2019. [CrossRef] [Google Scholar]
- I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, et al., “Generative adversarial nets,” in Advances in Neural Information Processing Systems (NeurIPS), vol. 27, 2014. [Google Scholar]
- T. Karras, S. Laine and T. Aila, “A style-based generator architecture for generative adversarial networks,” in Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR), 2019, pp. 4401–4410. [Google Scholar]
- Yan Congkuan, Zhu Dequan, Meng Fankai, Yang Yuqing, Tang Qixing, Zhang Aifang, Liao Juan, “Rice leaf disease image enhancement method based on improved CycleGAN,” Smart Agriculture, vol. 6, no. 6, pp. 96–108, 2024. [Google Scholar]
- Q. Dai, Y. Guo, Z. Li, S. Song, S. Lyu, D. Sun, et al., “Citrus disease image generation and classification based on improved FastGAN and EfficientNet-B5,” Agronomy, vol. 13, no. 4, p. 988, 2023. [Google Scholar]
- D. P. Kingma and M. Welling, “Auto-encoding variational Bayes,” arXiv preprint arXiv:1312.6114, Dec. 2013. [Google Scholar]
- J. Ho, A. Jain and P. Abbeel, “Denoising diffusion probabilistic models,” in Advances in Neural Information Processing Systems (NeurIPS), vol. 33, pp. 6840–6851, 2020. [Google Scholar]
- P. Dhariwal and A. Nichol, “Diffusion models beat GANs on image synthesis,” in Advances in Neural Information Processing Systems (NeurIPS), vol. 34, pp. 8780–8794, 2021. [Google Scholar]
- D. P. Hughes and M. Salathé, “PlantVillage Dataset,” Mendeley Data, V1, 2015. [Online]. Available: https://data.mendeley.com/datasets/tywbtsjrjv/1 [Google Scholar]
- M. Bińkowski, D. J. Sutherland, M. Arbel and A. Gretton, “Demystifying MMD GANs,” arXiv preprint arXiv:1801.01401, Jan. 2018. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.