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Medical image processing is one of the most important topics in the field of the Internet of Medical Things (IoMT).
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S. J. Pan and Q. Yang, “A survey on transfer learning,” IEEE Transactions on knowledge and data engineering , vol. 22, no. 10, pp. 1345–1359, 2009
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2010
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W. Pan, N. N. Liu, E. W. Xiang, and Q. Yang, “Transfer learning to predict missing ratings via heterogeneous user feedbacks,” in Twenty-Second International Joint Conference on Artificial Intelligence , 2011
2011
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S. G. Armato III, G. McLennan, L. Bidaut, M. F. McNitt-Gray, C. R. Meyer, A. P. Reeves, B. Zhao, D. R. Aberle, C. I. Henschke, E. A. Hoffman et al. , “The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans,” Medical physics , vol. 38, no. 2, pp. 915–931, 2011
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A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems , 2012, pp. 1097–1105
2012
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2012
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Z. Zhang, P. Luo, C. C. Loy, and X. Tang, “Facial landmark detection by deep multi-task learning,” in European conference on computer vision . Springer, 2014, pp. 94–108
2014
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L. Ge, J. Gao, H. Ngo, K. Li, and A. Zhang, “On handling negative transfer and imbalanced distributions in multiple source transfer learning,” Statistical Analysis and Data Mining: The ASA Data Science Journal , vol. 7, no. 4, pp. 254–271, 2014
2014
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B. Tan, Y. Song, E. Zhong, and Q. Yang, “Transitive transfer learning,” in Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , 2015, pp. 1155–1164
2015
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O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in International Conference on Medical image computing and computer-assisted intervention . Springer, 2015, pp. 234–241
2015
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B. Sun and K. Saenko, “Deep coral: Correlation alignment for deep domain adaptation,” in European conference on computer vision . Springer, 2016, pp. 443–450
2016
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H.-C. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, and R. M. Summers, “Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning,” IEEE transactions on medical imaging , vol. 35, no. 5, pp. 1285–1298, 2016
2016
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D. S. Kermany, M. Goldbaum, W. Cai, C. C. Valentim, H. Liang, S. L. Baxter, A. McKeown, G. Yang, X. Wu, F. Yan et al. , “Identifying medical diagnoses and treatable diseases by image-based deep learning,” Cell , vol. 172, no. 5, pp. 1122–1131, 2018
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V. Cheplygina, M. de Bruijne, and J. P. Pluim, “Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis,” Medical image analysis , vol. 54, pp. 280–296, 2019
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J. N. Taroni, P. C. Grayson, Q. Hu, S. Eddy, M. Kretzler, P. A. Merkel, and C. S. Greene, “Multiplier: a transfer learning framework for transcriptomics reveals systemic features of rare disease,” Cell systems , vol. 8, no. 5, pp. 380–394, 2019
2019
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Cited alongside, same era.
W. Zhang, R. Li, T. Zeng, Q. Sun, S. Kumar, J. Ye, and S. Ji, “Deep model based transfer and multi-task learning for biological image analysis,” IEEE transactions on Big Data , 2016
2016
Cited alongside, same era.
M. Xie, N. Jean, M. Burke, D. Lobell, and S. Ermon, “Transfer learning from deep features for remote sensing and poverty mapping,” in Thirtieth AAAI Conference on Artificial Intelligence , 2016
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2016, pp. 770–778
2016
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B. Tan, Y. Zhang, S. J. Pan, and Q. Yang, “Distant domain transfer learning,” in Thirty-First AAAI Conference on Artificial Intelligence , 2017
2017
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M. Long, H. Zhu, J. Wang, and M. I. Jordan, “Deep transfer learning with joint adaptation networks,” in Proceedings of the 34th International Conference on Machine Learning-Volume 70 . JMLR. org, 2017, pp. 2208–2217
2017
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2017
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Later among the works it cites.
S. Niu, J. Wang, Y. Liu, and H. Song, “Transfer learning based Data-Efficient machine learning enabled classification,” in The 6th International Conference on Cloud and Big Data Computing (2020) (CBDCom 2020) , Aug. 2020
2020
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N. S. S. H. Liu Y., Wang J., “(2020) deep learning enabled reliable identity verification and spoofing detection,” 2020
2020
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A. Bernheim, X. Mei, M. Huang, Y. Yang, Z. Fayad, N. Zhang, K. Diao, B. Lin, X. Zhu, K. Li, S. Li, H. Shan, A. Jacobi, and M. Chung, “Chest ct findings in coronavirus disease-19 (covid-19): Relationship to duration of infection,” Radiology , vol. 295, p. 200463, 02 2020
2020
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X. He, X. Yang, S. Zhang, J. Zhao, Y. Zhang, E. Xing, and P. Xie, “Sample-efficient deep learning for covid-19 diagnosis based on ct scans,” medrxiv , 2020
2020
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2020
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