Satellite imagery for dummies.
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Updated
Mar 12, 2022 - Python
Satellite imagery for dummies.
Satellite Image Classification using semantic segmentation methods in deep learning
A python package that extends Google Earth Engine.
1st place solution to the Satellite Remote Sensing Image Change Detection Challenge hosted by SenseTime
AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.
DeepGlobe Land Cover Classification Challenge遥感影像语义分割
Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.
A QGIS plugin tool using Segment Anything Model (SAM) to accelerate segmenting or delineating landforms in geospatial raster images.
Pre-trained VGG-Net Model for image classification using tensorflow
Build a machine learning model to detect change in Multi-temporal Satellite Images 🌍
ParaView plugins
Automatically create machine learning datasets from satellite images
🗺️ To be able to discover, request and use aggregate imagery products based on landsat-8/9, Sentinel 2 and other sensors from within QGIS, using the <geosys/> API.
Implementing a remote sensing object detector using Tensorflow object detection API
Python package to process images from Landsat tellites and return geographic information, cloud mask, numpy array, geotiff.
Estimate the stereoscopic capacity (B/H) of pairs of images from the Pleiades or SPOT6-7 satellites
Build a machine learning model to detect change in Multi-temporal Satellite Images 🌍
[NeurIPS 2023] Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator
Region of Interest detection on satellite images for weather changes
A package to facilitate access to the Arlula Imagery Marketplace API
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