1. Abbet, C., et al.: Self-rule to adapt: Learning generalized features from sparsely-labeled data using unsupervised domain adaptation for colorectal cancer tissue phenotyping. In: Medical Imaging with Deep Learning (2021)
2. Alsubaie, N., Trahearn, N., Ahmed Raza, S., Rajpoot, N.M.: A discriminative framework for stain deconvolution of histopathology images in the maxwellian space. In: MIUA, pp. 132–137 (2015)
3. Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning, pp. 1597–1607. PMLR (2020)
4. Chen, X., Fan, H., Girshick, R.B., He, K.: Improved baselines with momentum contrastive learning. CoRR abs/2003.04297 (2020). https://arxiv.org/abs/2003.04297
5. Foote, A., Asif, A., Rajpoot, N., Minhas, F.: REET: robustness evaluation and enhancement toolbox for computational pathology. Bioinformatics (Oxford, England) 38, 3312–3314 (2022)