Lingcao Huang's repositories
Landuse_DL
Land use classification or Landform delineation on remote sensing images. Specifically, this repo is to delineate landforms due to the thawing of ice-rich permafrost using Deep Learning.
DeeplabforRS
Automatic Mapping of Thermokarst Landforms from Remote Sensing Images Using Deep Learning: A Case Study in the Northeastern Tibetan Plateau
ChangeDet_DL
Change detection of the earth's surface using deep learning algorithms
labelEarth
Crowdsourcing system for labeling objects on the Earth's surface
rs_data_proc
scripts for pre-processing different sources of remote sensing images
rsBuildingSeg_python3
my final project of Deep Learning course at Chinese University of Hong Kong. The target of this project is to extract buildings polygon from high resolution optical remote sensing image. The dataset is from SpaceNet
run_isce_insar
SAR and InSAR process by using ISCE, and Post-Processing
asarapi
Search and download ERS-1, ERS-2, and Envisat products.
contrastive-unpaired-translation
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
CSF
LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation
esa-online-catalogue
Scrape ESA Online Catalogue into a local SQLite database
GEE_HotSpot
Google Earthengine HotSpot Regions of Permafrost Change Production and Visualization
HIP-Examples
Examples for HIP
intermediate-node-course
an intermediate node.js course
labelEarthServer
host data on a server for labelEarth
mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
node-express-course
An introduction to Node.js and Express.js servers
pygeohydro
A part of HyRiver software stack for accessing hydrology data through web services
rmacc22-dask-hpc
Tutorial materials from the Dask on HPC session at the RMACC 2022 Symposium
rsBuildingMapping
Building mapping from SpaceNet dataset.
rsBuildingSeg
my final project of Deep Learning course at Chinese University of Hong Kong. The target of this project is to extract building polygons from high resolution optical remote sensing images. The dataset are from SpaceNet
rts-site-data-review
Compiling and reviewing the study sites for retrogressive thaw slumps
segment-anything-largeImage
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
SSL4EO-S12
SSL4EO-S12: a large-scale dataset for self-supervised learning in Earth observation
ultralytics
YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite
validate-thaw-slump
validate retrogressive thaw slumps using multiple online maps