Towards an efficient 3D model estimation methodology for aerial and ground images
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Updated
Oct 2, 2017
Towards an efficient 3D model estimation methodology for aerial and ground images
Aerial Image segmentation using different EfficientNet based backbone encoders with UNet on Massachusetts Building and Road dataset
Officiel implementation of the paper " FlightScope: A Deep Comprehensive Assessment of Aircraft Detection Algorithms in Satellite Imagery "
Mangrove Classification from Aerial Imagery
Sealion detection and classification on air-view images
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images.
Serverless Landsat map tiles from mosaics of Cloud-Optimized GeoTIFFs
Web-Interface-GCP-Finder é um projeto que pretende simplificar a utilização da ferramenta GCP Finder, que em sí é um programa capaz de identificar Aruco Markers em imagens.
Native (unofficial) WebApp for Google Maps, built with Tauri
Python scripts to detect objects in georeferenced images using the Detectron2 deep learning platform.
Get started with landcover classification using machine learning and satellite or aerial imagery.
Zero shot image classification
Semantic Classification of Aerial Images (RGB) from Drones using Unet
This repository provides an implementation of semantic segmentation for road networks using PyTorch and the U-Net architecture. It focuses specifically on processing aerial images from the Massachusetts dataset.
Create an image of a random location in the world (from an XYZ server)
Laguerre-Gauss Preprocessing: Line Profiles as Image Features
Coding used to process drone-captured Near-Infrared Images into Normalised Differential Vegetation Index (NDVI) greyscale images which are then further processed using both a segmentation of ndvi around the tomb region followed by a contour overlay in the perimeter of the tombs. Version 2 uses a standard contour, Version 4 is an attempt, with li…
SkyScenes: A Synthetic Dataset for Aerial Scene Understanding
Modified source code of published article: Real-ESRGAN: A deep learning approach for general image restoration and its application to aerial images
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