有限数据量如何最大化提升模型效果？百度工程师构建数据增强服务

[4]:Cubuk E D, Zoph B, Shlens J, et al. Randaugment: Practical automated data augmentation with a reduced search space[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2020: 702-703.

[5]:Zhang X, Wang Q, Zhang J, et al. Adversarial autoaugment[J]. arXiv preprint arXiv:1912.11188, 2019.

[6]:Li Y, Hu G, Wang Y, et al. DADA: Differentiable Automatic Data Augmentation[J]. arXiv preprint arXiv:2003.03780, 2020.
[7]:Jaderberg M, Dalibard V, Osindero S, et al. Population based training of neural networks[J]. arXiv preprint arXiv:1711.09846, 2017.

[8]:https://paddleclas.readthedocs.io/zh_CN/latest/advanced_tutorials/image_augmentation/ImageAugment.html#id6

[9]:https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/autoaugment

[10]: Zoph B, Cubuk E D, Ghiasi G, et al. Learning data augmentation strategies for object detection[J]. arXiv preprint arXiv:1906.11172, 2019.

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