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Recently, foundation models have been introduced demonstrating various tasks in the field of computer vision.
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N. Houlsby, A. Giurgiu, S. Jastrzebski, B. Morrone, Q. De Laroussilhe, A. Gesmundo, M. Attariyan, and S. Gelly, “Parameter-efficient transfer learning for nlp,” in International Conference on Machine Learning . PMLR, 2019, pp. 2790–2799
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S. Fu, Y. Lu, Y. Wang, Y. Zhou, W. Shen, E. Fishman, and A. Yuille, “Domain adaptive relational reasoning for 3d multi-organ segmentation,” in Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part I 23 . Springer, 2020, pp. 656–666
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2021
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2021
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2021
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2021
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Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, and B. Guo, “Swin transformer: Hierarchical vision transformer using shifted windows,” in Proceedings of the IEEE/CVF international conference on computer vision , 2021, pp. 10 012–10 022
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2021
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2021
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2021
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H. Wang, S. Xie, L. Lin, Y. Iwamoto, X.-H. Han, Y.-W. Chen, and R. Tong, “Mixed transformer u-net for medical image segmentation,” in ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2022, pp. 2390–2394
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2023
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2023
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2023
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2023
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