1huang

1huang's Stars

• rahulgite94/Compressive-Sensing-and-Deep-Learning-Framework

  We propose Compressive Sensing and Deep Learning framework (CS-DL) for multiple satellite sensor based data fusion. It’s aims to improve spatial and temporal resolution for long term analysis. Compressive Sensing is used as an initial guess to combine data from multiple sources. Deep Learning model, using Long Short Term Memory Neural Network (LSTM/RNN) refines and further improves the resulting data fusion output from CS. Our CS-DL framework has been tested to fuse CO2 from the NASA Orbiting Carbon Observatory-2 (OCO-2) and the JAXA Greenhouse gases from Orbiting Satellites (GOSAT). It achieves lower errors and high correlation compared with the original data. This work demonstrates the use of CS-DL for fusing CO2 from NASA Orbiting Carbon Observatory-3 and GOSAT2 at higher resolution.

  Language:Jupyter Notebook204

• dng55/Remote_sensing_CH4

  Combining remote sensing products from Google Earth Engine with a methane emission model to characterize surface conditions of methane hotspots in wetlands.

  Language:Jupyter Notebook52

• r-barnes/richdem

  High-performance Terrain and Hydrology Analysis

  Language:C++25364

• AlexandreWadoux/non_stationary_variance_kriging

  Kriging with external drift and non-stationary variance

  Language:R71

• flashlxy/PyMICAPS

  气象数据可视化，用matplotlib和basemap绘制micaps数据

  Language:Python370156

• danfenghong/IEEE_TGRS_MDL-RS

  Danfeng Hong, Lianru Gao, Naoto Yokoya, Jing Yao, Jocelyn Chanussot, Qian Du, Bing Zhang. More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification, IEEE TGRS, 2021, 59(5): 4340-4354.

  Language:Python9921

• danfenghong/IEEE_TGRS_GCN

  Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Graph Convolutional Networks for Hyperspectral Image Classification, IEEE Trans. Geosci. Remote Sens., 2021, 59(7): 5966-5978.

  Language:Python22767

• mahmad00/GELM-AE-AL

  The following demo comes for two papers "Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification" and "Multi-layer Extreme Learning Machine-based Autoencoder for Hyperspectral Image Classification".

  Language:MATLAB43

• liubing220524/ResNet-for-hyperspectral-image-classification

  Res-3D-CNN for hyperspectral image classification.

  Language:Python4418