1. Afshar, P., Heidarian, S., Naderkhani, F., Oikonomou, A., Plataniotis, K.N., Mohammadi, A.: COVID-CAPS: a capsule network-based framework for identification of COVID-19 cases from X-ray images. Pattern Recogn. Lett. 138, 638–643 (2020)
2. Ahmed, K.B., Goldgof, G.M., Paul, R., Goldgof, D.B., Hall, L.O.: Discovery of a generalization gap of convolutional neural networks on COVID-19 X-rays classification. IEEE Access 9, 72970–72979 (2021)
3. Bahdanau, D., Cho, K.H., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: 3rd International Conference on Learning Representations, ICLR 2015 (2015)
4. Bai, H.X., et al.: Performance of radiologists in differentiating COVID-19 from non-COVID-19 viral pneumonia at chest CT. Radiology 296(2), E46–E54 (2020)
5. 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)