GCN-based MIL: multi-instance learning utilizing structural relationships among instances-Reference-Cited by-同舟云学术

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GCN-based MIL: multi-instance learning utilizing structural relationships among instances

Published:2024-05-20 Issue:6-7 Volume:18 Page:5549-5561
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Ma Yangling,Luo Yixin,Yang Zhouwang

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-024-03254-6.pdf

Reference45 articles.

1. Zhou, Z.-H., Sun, Y.-Y., Li, Y.-F.: Multi-instance learning by treating instances as non-iid samples. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 1249–1256. ACM (2009)

2. Combalia, M., Vilaplana, V.: Monte-Carlo sampling applied to multiple instance learning for histological image classification. In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, pp. 274–281. Springer, Berlin (2018)

3. Wang, Y., Wang, G.A., Fan, W., Li, J.: A deep learning based pipeline for image grading of diabetic retinopathy. In: International Conference on Smart Health, pp. 240–248. Springer (2018)

4. Xu, G., Song, Z., Sun, Z., Ku, C., Yang, Z., Liu, C., Wang, S., Ma, J., Xu, W.: Camel: a weakly supervised learning framework for histopathology image segmentation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 10682–10691 (2019)

5. Wang, H., Jiang, D., Zhang, H., Wang, Y., Yang, L., Kerr, D.J., Zhang, Y.: An explainable coarse-to-fine survival analysis method on multi-center whole slide images. IEEE Trans. Artif. Intell. (2023). https://doi.org/10.1109/TAI.2023.3285855

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1. Graph Neural Network Based Multi-Instance Learning with Graph Structure Learning;2024 7th International Conference on Artificial Intelligence and Big Data (ICAIBD);2024-05-24

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