U-Net和Hourglass采用高到低和低到高层特征图双向融合的方式以递归式结构得到高分辨率特征图,网络复杂且效率较低。本文选取高分辨率网络(High-Resolution Network, HRNet)[24]作为特征提取骨干网络获得具有丰富细粒度信息的特征。如图2所示,HRNet能从输入到输出始终保持高分辨率特征图,对于密集排列或者有轻微遮挡和重叠的...
As a result, a spatialattention residual U-Net architecture is proposed to enhance the effectiveness of waterbody segmentation. The suggested approach reweights the feature representation spatiallyto obtain data on water features, using U-Net as the network architecture. The feature of thewater zone...
We introduce the semantic segmentation method into FRA-SAR segmentation for the first time. The experiments verify the effectiveness and superiority of SAR FRA segmentation based on the proposed SA-U-Net++ model compared with the existed semantic segmentation approaches. (C) 2021 Society of Photo-...
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. February 2018. Available online: http://arxiv.org/abs/1802.02611 (accessed on 23 October 2023). Fan, T.; Wang, G.; Li, Y.; Wang, H. Ma-net: A multi-scale attention network for liver and tumor segmentation...