The following publications are possibly variants of this publication:
- Bi-SANet - Bilateral Network with Scale Attention for Retinal Vessel SegmentationYun Jiang, Huixia Yao, Zeqi Ma, Jingyao Zhang. symmetry, 13(10):1820, 2021. [doi]
- Scale-aware dense residual retinal vessel segmentation network with multi-output weighted lossJiwei Wu, Shibin Xuan. bmcmi, 23(1):100, December 2023. [doi]
- PCRTAM-Net: A Novel Pre-Activated Convolution Residual and Triple Attention Mechanism Network for Retinal Vessel SegmentationHuadeng Wang, Zi-Zheng Li, Idowu Paul Okuwobi, Bingbing Li, Xipeng Pan, Zhenbing Liu, Rushi Lan, Xiao-Nan Luo. jcst, 38(3):567-581, June 2023. [doi]
- CRAUNet: A cascaded residual attention U-Net for retinal vessel segmentationFangfang Dong, Dengyang Wu, Chenying Guo, Shuting Zhang, Bailin Yang, Xiangyang Gong. cbm, 147:105651, 2022. [doi]
- Attention-inception-based U-Net for retinal vessel segmentation with advanced residualHuadeng Wang, Guang Xu, Xipeng Pan, Zhenbing Liu, Ningning Tang, Rushi Lan, Xiaonan Luo. cee, 98:107670, 2022. [doi]