five

Labeled satellite imagery for training machine learning models that predict the suitability of semantic segmentation model outputs for shoreline extraction

收藏
U.S. Geological Survey2026-04-23 收录
下载链接:
https://cmgds.marine.usgs.gov/data-releases/datarelease/10.5066-P1N4VI7H/
下载链接
链接失效反馈
官方服务:
资源简介:
A collection of data releases containing labeled satellite imagery for the purpose of training Machine Learning models to automate the task of shoreline extraction from satellite imagery. Shoreline mapping from satellite imagery, known as Satellite-Derived Shorelines or SDS, has the potential to transform coastal shoreline mapping for erosion hazard mapping and coastal resource assessment, among many potential uses. Automation of such tasks using Machine Learning is a crucial component of cost-saving and quality assurance for large-scale routine shoreline mapping. The associated satellite images with labeled classifications (https://doi.org/10.5066/P13EOBZQ) and image suitability (https://doi.org/10.5066/P14MDKVJ) datasets are available.
提供机构:
Contractor to the United States Geological Survey
二维码
社区交流群
二维码
科研交流群
商业服务