Automatic Water-Body Segmentation From High-Resolution Satellite Images via Deep Networks 笔记 出发点 水域分割是遥感的基本任务。 传统的方法依赖光谱,只能处理分辨率低图像。而分辨率强的图片,包含更多细节。 不同数据传感器获得数据,方法的鲁棒性得到考验。 主要的创新点 提出一个新的分割网络RRF DeconvNet 网络(...
In this paper, the water body segmentation is carried out by creating and training a deep learning network called SegNet which is derived from VGG16. Pixel Labeled Data of the input dataset are used for training the deep hidden units and the learned features are used to extract the water ...
structures as water, UNet++, U2-Net, UNeXt misjudge more water as non-water, and and PSPNet have severe distortion, while EU-Net and DeepLabV3 + provide more accurate segmentation, but DeepLabV3+ is not as good as EU-Net in boundary handling. In Fig.9(f1), while all models pe...
Rich CNN Features for Water-Body Segmentation from Very High Resolution Aerial and Satellite Imagery 来自 Semantic Scholar 喜欢 0 阅读量: 280 作者: C Nie 摘要: Extracting water-bodies accurately is a great challenge from very high resolution (VHR) remote sensing imagery. The boundaries of a ...
In this regard to address a major hazard of today which is drought monitoring, this paper focuses on developing an effective water segmentation method for such geospatial cloud web services. The Landsat 8 images of Sambhar lake region has been chosen for exploiting the water segmentation results. ...
Such a long-tailed distribution is common for semantic segmentation datasets even if the number of images that contain specific label are pre-controlled. Such frequency distribution for pixels would be inevitable for objects existing in real-world. Taking "water tower" as an example, despite having...
Introduction: The 2020 Gaofen challenge water body segmentation dataset was released by the 2020 Gaofen Challenge committee, which is the current only specific high-resolution optical dataset for water body classification. The dataset contains 1000 RGB images from the GF-2 satellite, of which the ...
Deep-Learning-Based Multispectral Satellite Image Segmentation for Water Body Detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. doi: 10.1109/JSTARS.2021.3098678. Google Scholar Zhang, 1988 W. Zhang Shift-invariant pattern recognition neural network and its optical architecture Proc. Ann....
Second, an object-oriented method is used for image segmentation. A rough initial waterbody information extraction is performed based on spectral information, and then refined based on the characteristic knowledge. Third, noise is eliminated and holes are filled in the images of the refined water...
The aim of this study was to establish a workflow for automated MRI-based segmentation of visceral (VAT) and subcutaneous adipose tissue (SCAT) and lean tissue water (LTW) in a B16 melanoma animal model, monitor diseases progression and transfer the protocol to human melanoma patients for ...