This example first shows you how to perform semantic segmentation using a pretrained U-Net and then use the segmentation results to calculate the extent of vegetation cover. Then, you can optionally train a U-Net network on the Hamlin Beach State Park data set using a patch-based training ...
In the research of automatic interpretation of remote sensing images, semantic segmentation based on deep convolutional neural networks has been rapidly developed and applied, and the feature segmentation accuracy and network model generalization ability have been gradually improved. However, most of the ...
This example first shows you how to perform semantic segmentation using a pretrained U-Net and then use the segmentation results to calculate the extent of vegetation cover. Then, you can optionally train a U-Net network on the Hamlin Beach State Park data set using a patch-based training met...
MSNet: multispectral semantic segmentation network for remote sensing images. GIScience & Remote Sensing 59, 1177–1198. https://doi.org/10.1080/15481603.2022.2101728 [Paper] Abstract In the research of automatic interpretation of remote sensing images, semantic segmentation based on deep convolutional...
Semantic segmentation of land cover from high resolution multispectral satellite images by spectral-spatial convolutional neural networkEkrem SaraliogluOguz Gungor
Extensive research on retinal layer segmentation (RLS) using deep learning (DL) is mostly approaching a performance plateau, primarily due to reliance on structural information alone. To address the present situation, we conduct the first study on the impact of multi-spectral information (MSI) on ...
Semantic Segmentation of Natural Materials on a Point Cloud Using Spatial and Multispectral Features The characterization of natural spaces by the precise observation of their material properties is highly demanded in remote sensing and computer vision. Th... JM Jurado,JL Cárdenas,CJ Ogayar,... -...
The deep learning model incorporates a semantic segmentation gated full fusion module that integrates a dual attention mechanism. This module enhances the capture of detailed texture information, optimally allocates spectral weights, and improves the model’s ability to distinguish between similar ...
Rashkovetsky D, Mauracher F, Langer M, Schmitt M (2021) Wildfire detection from multisensor satellite imagery using deep semantic segmentation. IEEE J Selected Topic Appl Earth Observ Remote Sensing 14:7001–7016 Article Google Scholar Castagna J, Senatore A, Pellis G, Vitullo M, Bencardino...
来自 Semantic Scholar 喜欢 0 阅读量: 123 作者:J Chen,J Li,D Pan,Q Zhu,Z Mao 摘要: This paper presents a new approach to multiscale segmentation of satellite multispectral imagery using edge information. The Canny edge detector is applied to perform multispectral edge detection. The detected ...