Oleg Zabluda's blog
Tuesday, September 05, 2017
 
Deep learning for satellite imagery via image segmentation
Deep learning for satellite imagery via image segmentation
"""
In the recent Kaggle competition Dstl Satellite Imagery Feature Detection our deepsense.io team won 4th place among 419 teams. We applied a modified U-Net – an artificial neural network for image segmentation.
[...]
Competition

The challenge was organized by the Defence Science and Technology Laboratory (Dstl), an Executive Agency of the United Kingdom’s Ministry of Defence on Kaggle platform. As a training set, they provided 25 high-resolution satellite images representing 1 km2 areas. The task was to locate 10 different types of objects:

Buildings
Miscellaneous manmade structures
Roads
Tracks
Trees
Crops
Waterway
Standing water
Large vehicles
Small vehicles
"""
https://deepsense.io/deep-learning-for-satellite-imagery-via-image-segmentation/

https://deepsense.io/deep-learning-for-satellite-imagery-via-image-segmentation/

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