Apr 19, 2023 � This article proposes a framework to introduce digital surface model (DSM) data for the unsupervised semantic segmentation of RSI.
These methods combine various remote sensing data to improve segmentation accuracy [41],. [42], such as DSM and normalized difference vegetation index/visible-�...
MTD is designed to produce fusion prediction maps by filtering interference information of DSM and yielding accurate segmentation masks of DSM and RSI.
Aug 16, 2022 � This study proposes a novel unsupervised domain adaptation semantic segmentation network (MemoryAdaptNet) for the semantic segmentation of HRS imagery.
Missing: DSM- Assisted
DSM-Assisted Unsupervised Domain Adaptive Network for Semantic Segmentation of Remote Sensing Imagery. Article. Jan 2023. Shunping Zhou � Yuting Feng�...
DSM-assisted unsupervised domain adaptive network for semantic segmentation of remote sensing imagery. S Zhou, Y Feng, S Li, D Zheng, F Fang, Y Liu, B Wan. IEEE�...
DSM-Assisted Unsupervised Domain Adaptive Network for Semantic Segmentation of Remote Sensing Imagery. IEEE Transactions on Geoscience and Remote Sensing.
In this paper, we address this issue and consider the challenge of domain adaptation in semantic segmentation of aerial images.
May 17, 2023 � Wan, “Dsm- assisted unsupervised domain adaptive network for semantic segmenta- tion of remote sensing imagery,” IEEE Transactions on�...
Unsupervised domain adaptation (UDA) for semantic segmentation aims to adapt a segmentation model trained on the labeled source domain�...