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18 search results found

Techniques ⭐ 7,678

Techniques for deep learning with satellite & aerial imagery

Awesome Geospatial ⭐ 3,703

Long list of geospatial tools and resources

Awesome Satellite Imagery Datasets ⭐ 3,381

🛰️ List of satellite image training datasets with annotations for computer vision and deep learning

GRASS GIS - free and open-source geospatial processing engine

Awesome_satellite_benchmark_datasets ⭐ 231

Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.

Rasterframes ⭐ 226

Geospatial Raster support for Spark DataFrames

AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.

Rsgislib ⭐ 130

Remote Sensing and GIS Software Library; python module tools for processing spatial data.

Semi-automatic tool for manual segmentation of multi-spectral and geo-spatial imagery.

Pytorch Psetae ⭐ 98

PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"

Crop Type Detection Iclr 2020 ⭐ 62

Winning Solutions from Crop Type Detection Competition at CV4A workshop, ICLR 2020

Downscale Satellitelst ⭐ 35

A python class for enhancing the spatial resolution of satellite-derived Land Surface Temperatures (LST) using statistical downscaling.

Pre Lt Raster Frames ⭐ 19

Spark DataFrames for earth observation data

Dincae.jl ⭐ 18

DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data in satellite observations.

Causalimages Software ⭐ 15

causalimages: An R package for performing causal inference with image and image sequence data with a JAX backend

Picterra Python ⭐ 14

Picterra Python API Client

Model_ecaas_agrifieldnet_gold ⭐ 10

AgriFieldNet Model for Crop Detection from Satellite Imagery

Making Deep Learning for Earth Observation more easy

Satsense ⭐ 10

Satsense is a Python library for land use/cover classification using satellite imagery

Floating Marine Debris Data ⭐ 6

This repository contains data from Sentinel-2 imagery on floating marine debris, with annotations for six debris classes, including plastic, driftwood, seaweed, pumice, sea snot, and sea foam.

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