EGFNet: Efficient guided feature fusion network for skin cancer lesion segmentation-Reference-Cited by-同舟云学术

EGFNet: Efficient guided feature fusion network for skin cancer lesion segmentation

Published:2022-03-04 Issue: Volume: Page:
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Container-title:2022 the 6th International Conference on Innovation in Artificial Intelligence (ICIAI)
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Author:

Fan Rui¹,Wang Zhiqiang¹,Zhu Qing¹

Affiliation:

1. Beijing University Of Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3529466.3529482

Reference14 articles.

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3. Ronneberger Olaf “U-Net: Convolutional Networks for Biomedical Image Segmentation.” MICCAI (2015). Ronneberger Olaf “U-Net: Convolutional Networks for Biomedical Image Segmentation.” MICCAI (2015).

4. Badrinarayanan Vijay “SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (2017): 2481-2495. Badrinarayanan Vijay “SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (2017): 2481-2495.

5. Xie Yutong “A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification.” IEEE Transactions on Medical Imaging 39 (2020): 2482-2493. Xie Yutong “A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification.” IEEE Transactions on Medical Imaging 39 (2020): 2482-2493.

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