Packages intended to assist in the preprocessing of SpaceNet satellite imagery data corpus to a format that is consumable by machine learning algorithms.
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Updated
Jul 2, 2019 - Python
Packages intended to assist in the preprocessing of SpaceNet satellite imagery data corpus to a format that is consumable by machine learning algorithms.
Building detection from the SpaceNet dataset by using Mask RCNN.
Winning Solutions from SpaceNet Road Detection and Routing Challenge
Building detector algorithms from second SpaceNet Challenge
Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.
python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.
This software is a modification of Visualizer from Spacenet competition for road extraction. I made it work for DeepGlobe dataset also.
Mask RCNN trained to detect buildings from the SpaceNet Off Nadir dataset
Building detection from the SpaceNet dataset using UNet.
Automatic Building Footprint Segmentation: U-Net Production-Level API
Tools for Implementation of STAC SPEC for SpaceNet dataset https://github.com/radiantearth/stac-spec/tree/dev
5th-place solution for SpaceNet-8: Flood Detection Challenge Using Multiclass Segmentation
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