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calvin-sjtu

calvindrstar.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

hello-world

a new start

incertae

Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments

kite

InSAR unwrapped surface displacement processing.

pinns_rre

Physics-informed neural networks for the Richardson-Richards equation

robosat

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

rs_buildings_extraction

本项目已不再维护，所有功能已迁移至robosat_geoc，更好更强大，可以点击链接查看。

vector-map-generation-from-aerial-imagery-using-deep-learning-geospatial-unet

We propose a simple yet efficient technique to leverage semantic segmentation model to extract and separate individual buildings in densely compacted areas using medium resolution satellite/UAV orthoimages. We adopted standard UNET architecture, additionally added batch normalization layer after every convolution, to label every pixel in the image.