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sanwen211314's Projects

sgsgmm icon sgsgmm

Hyperspectral Unmixing With Gaussian Mixture Model And Spatial Group Sparsity

sgsnmf_tgrs icon sgsnmf_tgrs

X. Wang, Y. Zhong, L. Zhang, and Y. Xu, “Spatial Group Sparsity Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 11, pp.6287-6304, 2017.

shred icon shred

Matlab code for estimating Hyperspectral data from RGB/Multispectral images

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Prediction of circRNA-disease associations based on inductive matrix completion.

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Prediction of lncRNA-disease associations based on inductive matrix completion

simplelocal icon simplelocal

Implementation of SimpleLocal for Local Cut Improvement in Graphs

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Structured Light Compressive Sensing Project

spectralcov-gp-mtgp icon spectralcov-gp-mtgp

Gaussian Processes for Vegetation Parameter Estimation from Hyperspectral Data with Limited Ground Truth

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We put the matlab code of our algorithms SVFW-M and SPIDER-FW-M in AAAI 2020 to implement the low-rank matrix completion experiment here.

spider_plot icon spider_plot

Create a spider or radar plot with individual axes.

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Massive MIMO Channel Estimation for Millimeter Wave Systems via Matrix Completion

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Smoothed rank function for matrix completion

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Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018)

sslgraphlabelling icon sslgraphlabelling

Source for various Semi Supervised graph labelling methods that I wrote for experimenting with Harmonic Energy Minimization, linear programming for max-flow/min-cut and quadratic programming for Graph Laplacian methods

stacked_autoencoder-basic_version icon stacked_autoencoder-basic_version

用 MATLAB 实现深度学习网络中的 stacked auto-encoder:使用AE variant(de-noising / sparse / contractive AE)进行预训练,用BP算法进行微调

stone icon stone

Implementation of the STOne transform for compressed sensing video

sttc-code icon sttc-code

the code is for the paper Image Completion Using Low Tensor Tree Rank and Total Variation Minimization

subm icon subm

Sparse unmixing of hyperspectral data with bandwise model

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