A Light-Weight Context-Aware Self-Attention Model for Skin Lesion Segmentation-Reference-Cited by-同舟云学术

A Light-Weight Context-Aware Self-Attention Model for Skin Lesion Segmentation

Published:2019 Issue: Volume: Page:501-505
ISSN:0302-9743
Container-title:PRICAI 2019: Trends in Artificial Intelligence
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Author:

Ma Dongliang,Wu Hao,Sun Jun,Yu Chunjing,Liu Li

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-29894-4_40

Reference12 articles.

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2. Bi, L., Kim, J., Ahn, E., Feng, D.: Automatic skin lesion analysis using large-scale dermoscopy images and deep residual networks. arXiv preprint arXiv:1703.04197 (2017)

3. Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 801–818 (2018)

4. Codella, N.C.F., et al.: Skin lesion analysis toward melanoma detection: a challenge at the 2017 international symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC). In: IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp. 168–172. IEEE (2018)

5. Ding, H., Jiang, X., Shuai, B., Liu, A.Q., Wang, G.: Context contrasted feature and gated multi-scale aggregation for scene segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2393–2402 (2018)

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