A simple example of a machine learning library for land-cover classification
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Updated
Jan 20, 2022 - Python
A simple example of a machine learning library for land-cover classification
Crop type mapping solution for MAGO Project (NTUA)
A land cover classification task performed with machine learning modelling on Sentinel-2 data for Gibraltar.
Land cover classification in Tanzania using ensemble labels and high resolution Planet NICFI basemaps and Sentinel-1 time series.
Land Cover Classification for KAZA in Collaboration with WWF Space Science Germany
Multi-scale patch-wise semantic segmentation of satellite images using U-Net architecture.
Land cover classification hackathon during the OpenGeoHub Summer School 2023 in Poznan (Poland).
Implementation for "Global heterogeneous graph convolutional network: from coarse to refined land cover and land use segmentation"
Pixel-based and object-oriented land cover classifications of historical panchromatic Corona Spy satellite images
Classification of Sentinel-2 land cover multiband images through an ensamble of DNN
Code for our JSTARS paper "Semi-MCNN: A semisupervised multi-CNN ensemble learning method for urban land cover classification using submeter HRRS images"
Deep Learning based Land Cover Classification using Satellite Imagery
Work for BigEarthNet Data using resnet-50
My implementation of simple Land cover classification using Keras. This was part of one of my internships
Deep neural network for land cover use classification using Unet structure
Fundamentals of Remote Sensing and Earth Observation Course
Crop type mapping solution for MAGO Project (NTUA)
ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.
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