Techniques for deep learning with satellite & aerial imagery
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Updated
May 13, 2024
Techniques for deep learning with satellite & aerial imagery
Global shoreline mapping tool from satellite imagery
A curated list of resources focused on Machine Learning in Geospatial Data Science.
Spatiotemporal Arrays, Raster and Vector Data Cubes
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
The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.
AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.
GeoTorchAI: A Framework for Training and Using Spatiotemporal Deep Learning Models at Scale
DeepGlobe Land Cover Classification Challenge遥感影像语义分割
crop classification using deep learning on satellite images
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.
Beach-face slope estimation from satellite-derived shorelines, extension of the CoastSat toolbox.
Pre-trained VGG-Net Model for image classification using tensorflow
Build a machine learning model to detect change in Multi-temporal Satellite Images 🌍
How to use machine learning to find interesting places on satellite maps
python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.
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