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Masked autoencoder (MAE) has attracted unprecedented attention and achieves remarkable performance in many vision tasks.
Yu, Y., Acton, S.T.: Speckle reducing anisotropic diffusion. IEEE Transactions on image processing 11
2002
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Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. pp. 248–255. Ieee (2009)
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Park, M., Shin, J.H., Han, B.K., Ko, E.Y., Hwang, H.S., Kang, S.S., Kim, J.H., Oh, Y.L.: Sonography of thyroid nodules with peripheral calcifications. Journal of Clinical Ultrasound 37
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Wang, P., Patel, V.M., Hacihaliloglu, I.: Simultaneous segmentation and classification of bone surfaces from ultrasound using a multi-feature guided cnn. In: International conference on medical image computing and computer-assisted intervention. pp. 134–142. Springer (2018)
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Chen, X., Xie, S., He, K.: An empirical study of training self-supervised vision transformers. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 9640–9649 (2021)
2021
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Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B.: Swin transformer: Hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 10012–10022 (2021)
2021
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Niu, S., Liu, M., Liu, Y., Wang, J., Song, H.: Distant domain transfer learning for medical imaging. IEEE Journal of Biomedical and Health Informatics 25
2021
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Zhou, Y., Chen, H., Li, Y., Liu, Q., Xu, X., Wang, S., Yap, P.T., Shen, D.: Multi-task learning for segmentation and classification of tumors in 3d automated breast ultrasound images. Medical Image Analysis 70
2021
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An, J., Bai, Y., Chen, H., Gao, Z., Litjens, G.: Masked autoencoders pre-training in multiple instance learning for whole slide image classification. In: Medical Imaging with Deep Learning (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
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2022
Later among the works it cites.
Wang, X., Zhao, K., Zhang, R., Ding, S., Wang, Y., Shen, W.: Contrastmask: Contrastive learning to segment every thing. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 11604–11613 (2022)
2022
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2022
Later among the works it cites.
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He, K., Chen, X., Xie, S., Li, Y., Dollár, P., Girshick, R.: Masked autoencoders are scalable vision learners. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 16000–16009 (2022)
2022
Cited alongside, same era.
Ke, L., Danelljan, M., Li, X., Tai, Y.W., Tang, C.K., Yu, F.: Mask transfiner for high-quality instance segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4412–4421 (2022)
2022
Cited alongside, same era.
Li, Y., Mao, H., Girshick, R., He, K.: Exploring plain vision transformer backbones for object detection. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IX. pp. 280–296. Springer (2022)
2022
Cited alongside, same era.
Liu, Z., Mao, H., Wu, C.Y., Feichtenhofer, C., Darrell, T., Xie, S.: A convnet for the 2020s. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 11976–11986 (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Later among the works it cites.
2022
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Zhang, H., Liu, W., Shi, J., Chang, S., Wang, H., He, J., Huang, Q.: Maefe: Masked autoencoders family of electrocardiogram for self-supervised pretraining and transfer learning. IEEE Transactions on Instrumentation and Measurement 72
2022
Later among the works it cites.
2022
Later among the works it cites.
Chen, Z., Agarwal, D., Aggarwal, K., Safta, W., Balan, M.M., Brown, K.: Masked image modeling advances 3d medical image analysis. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1970–1980 (2023)
2023
Closest in time.
Xiao, J., Bai, Y., Yuille, A., Zhou, Z.: Delving into masked autoencoders for multi-label thorax disease classification. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 3588–3600 (2023)
2023
Closest in time.