1. Szegedy, C. et al. Going deeper with convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 1–9 (2015).
2. Kim, M., Zuallaert, J. & De Neve, W. Few-shot learning using a small-sized dataset of high-resolution fundus images for glaucoma diagnosis. In Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care 89–92 (ACM, 2017).
3. Maicas, G., Bradley, A. P., Nascimento, J. C., Reid, I. & Carneiro, G. Training medical image analysis systems like radiologists. In International Conference on Medical Image Computing and Computer-Assisted Intervention 546–554 (2018).
4. Vinyals, O., Blundell, C., Lillicrap, T., Wierstra, D. et al. Matching networks for one shot learning. In Advances in Neural Information Processing Systems 3630–3638 (2016).
5. Gupta, S., Girshick, R., Arbeláez, P. & Malik, J. Learning rich features from rgb-d images for object detection and segmentation. In European Conference on Computer Vision 345–360 (Springer, 2014).