Semantic segmentation models with good performance are crucial for the practical application of high-resolution remote-sensing images (RSI). Compared with nature images, in most cases the RSI dataset has the problem of unbalanced sample distribution between classes and unbalanced target size ratio. ...
Remote Sensing}, title={SAM-Assisted Remote Sensing Imagery Semantic Segmentation With Object and Boundary Constraints}, year={2024}, volume={62}, pages={1-16}, } @article{ma2023unsupervised, title={Unsupervised domain adaptation augmented by mutually boosted attention for semantic segmentation of ...
Deeplab v3-Plus Deeplab v3-plus for semantic segmentation of remote sensing(pytorch) 数据集: 在ISPRS Vaihigen 2D语义标签比赛数据集上评估了deeplab v3+的表现。该数据集由33张大小不同的高分辨率遥感影像组成,每张影像都是从德国Vaihigen市高空中获取的真正射影象(TOP)。在某种程度上,这个数据集的遥感印象与...
Semantic-segmentation-of-remote-sensing-image 基于深度学习关于遥感影像的语义分割 首先看一下数据集,包含原始影像与标签,实际的分辨率很大,这个只是缩略图。 影像数据是Landsat8卫星的,用五四三波段进行合成,并利用GS方法进行全色第八波段的融合。(Envi软件处理) 标签是通过矢量图层以ArcGIS软件来处理生成的。 此代码...
\1.标题:Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supervised Contrastive Learning Method \2.作者:Haifeng Li, Yi Li, Guo Zhang, Ruoyun Liu, Haozhe Huang, Qing Zhu, Chao Tao \3.作者单位:Central South University ...
**\1.标题:**Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supervised Contrastive Learning Method **\2.作者:**Haifeng Li, Yi Li, Guo Zhang, Ruoyun Liu, Haozhe Huang, Qing Zhu, Chao Tao ...
High-resolution remote sensing images usually contain complex semantic information and confusing targets, so their semantic segmentation is an important and challenging task. To resolve the problem of inadequate utilization of multilayer features by existing methods, a semantic segmentation method for remote...
论文题目:Seeing Beyond the Patch: Scale-Adaptive Semantic Segmentation of High-resolution Remote Sensing Imagery based on Reinforcement Learning 论文链接:https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_Seeing_Beyond_the_Patch_Scale-Adaptive_Semantic_Segmentation_of_High-resolution_Remote_ICCV_...
comment:: (MDANet)提出了可变形注意力,结合了稀疏空间采样策略和长程关系建模能力。 动机 高分辨率遥感图像的特点: 由于成像特点,它们往往呈现出冗余和噪声的地物细节。 HRRS图像中的多个地物由于类内方差高(例如,低矮植被和树木)、类间可分性低(例如,建筑)而难以区分。
[NIPS2021] LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation 近期在做一些遥感分割数据集调研,学习一下数据集文章的写作思路,在此做一些记录。 Introduction 随着社会和经济的不断发展,人类的生活环境逐渐分化,可分为城市区和农村区[8]。高空间分辨率(HSR)遥感技术可以帮助...