1. Badrinarayanan V, Kendall A, Cipolla R. 2016. Segnet: a deep convolutional encoder-decoder architecture for image segmentation. Proceedings of the European Conference on Computer Vision (ECCV); Amsterdam, The Netherlands.
2. Caron M, Touvron H, Misra I, Herve J´E, Mairal J, Bojanowski P, Joulin A. 2021. Emerging properties in self-supervised vision transformers. Proceedings of the IEEE/CVF international conference on computer vision; Virtual Conference. p. 9650–10.
3. Chaurasia A Culurciello E. 2017. Linknet: exploiting encoder representations for efficient semantic segmentation. arXiv preprint arXiv:1707.03718.
4. TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation
5. Chen L-C, Papandreou G, Kokkinos I, Murphy K, Yuille AL. 2017. Semantic image segmentation with deep convolutional nets and fully connected CRFs. Proceedings of the International Conference on Learning Representations; Palais des Congrès Neptune, Toulon, France.