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14 search results found

Techniques ⭐ 7,795

Techniques for deep learning with satellite & aerial imagery

Geotorchai ⭐ 428

GeoTorchAI: A Framework for Training and Using Spatiotemporal Deep Learning Models at Scale

Eye In The Sky ⭐ 248

Satellite Image Classification using semantic segmentation methods in deep learning

Geospatial Machine Learning ⭐ 196

A curated list of resources focused on Machine Learning in Geospatial Data Science.

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

Geo Sam ⭐ 127

A QGIS plugin tool using Segment Anything Model (SAM) to accelerate segmenting or delineating landforms in geospatial raster images.

Pytorch Psetae ⭐ 98

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

Imagetodem ⭐ 29

Generating Elevation Surface from a Single RGB Remotely Sensed Image Using Deep Learning

Crop Classification ⭐ 19

crop classification using deep learning on satellite images

Python For Remote Sensing ⭐ 15

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

Deepsatdata ⭐ 13

Automatically create machine learning datasets from satellite images

Urbanization Change Detection ⭐ 9

Urbanization detection using computer vision algorithms to reduce the reliance on the data of government surveys, which will speed up the policy making process.

Aerial Imagery ⭐ 8

Data Science Research Project: Map poverty using satellite images.

Pool Detection ⭐ 6

Detecting pools in satellite images

Object_detection_satellite_imagery_yolov8_dior ⭐ 6

Building a Yolov8n model from scratch and performing object detection in optical remote sensing images and videos.

Vec2instance ⭐ 5

This repository provides an implementation of Vec2Instance over the SpaceNet challenge AOI 2 (Vegas) building footprint dataset. Vec2Instance provides a framework for parametrization of instances, allowing convolutional neural networks to efficiently estimate the complex shapes of instances around their centroids.

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