terryyangwhu

terryyangwhu's Stars

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.6k3.3k

• davidfrantz/force

  Framework for Operational Radiometric Correction for Environmental monitoring

  Language:C17250

• MorvanZhou/Tensorflow-Tutorial

  Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

  Language:Python4.3k1.9k

• MrCPlusPlus/SRPPNN

  The model code of "Super-Resolution-Guided Progressive Pansharpening based on a Deep Convolutional Neural Network"

  Language:Python93

• lonl/CDBN

  Convolutional Deep Belief Networks with 'MATLAB','MEX','CUDA' versions

  Language:Matlab3525

• lisa-lab/DeepLearningTutorials

  Deep Learning Tutorial notes and code. See the wiki for more info.

  Language:Python4.1k2.1k

• matrachma/Deep-Belief-Network-for-Regression

  DBN for Regression Problem using Theano, NumPy, and Scikit-learn

  Language:Python239

• albertbup/deep-belief-network

  A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility

  Language:Python478212

• scutan90/DeepLearning-500-questions

  深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

  Language:JavaScript54.4k15.8k

• allenlu2008/PythonDemo

  虾神的Python示例代码库

  Language:Jupyter Notebook306178

• dragen1860/Deep-Learning-with-TensorFlow-book

  深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

  Language:Jupyter Notebook13.2k4.1k

• HannaMeyer/EcoMod_SpML

  Machine learning for spatial data: This repository contains the R-scripts for the analysis described in the paper "Importance of spatial predictor variable selection in machine learning applications - Moving from data reproduction to spatial prediction" submitted to Ecological Modelling

  Language:R117

• rasmusbergpalm/DeepLearnToolbox

  Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

  Language:Matlab3.8k2.3k

• ArianAzg/Application-of-Fractional-Calculus-in-Multispectral-Image-Fusion

  Application of fractional-order differentiation in multispectral image fusion

  Language:MATLAB14

• oscaragudelom/Pansharpening-IQA

  This repository contains all the details and results of the subjective study and image quality analyzer of pan-sharpened images.

  Language:Matlab91

• Decri/Multi-Scale-and-Depth-CNN-for-Pan-sharpening

  Matlab implementation of IEEE JSTARS article "A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening", along with the IEEE GRSL article DRPNN. MatConvNet and Caffe are required for full implementation.

  Language:Matlab2715

• lexcomber/GW-dists

  GW distance metric paper

  Language:R11

• Ziqi-Li/FastGWR

  Fast Geographically Weighted Regression (FastGWR)

  Language:Jupyter Notebook4619

• lexcomber/hyperlocalGWR

  Language:R11

• radosuav/pyDMS

  Python implementation of Data Mining Sharpener

  Language:Python4116

• harisw/STARFM_prediction

  Python implementation of STARFM(SPATIAL AND TEMPORAL ADAPTIVE REFLECTANCE FUSION MODEL) algorithm

  Language:Python259

• HPSCIL/cuSTARFM

  cuSTARFM is a GPU-enabled Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM)

  Language:Cuda6834

• GeoStat-Framework/PyKrige

  Kriging Toolkit for Python

  Language:Python759188

• pysal/mgwr

  Multiscale Geographically Weighted Regression (MGWR)

  Language:Jupyter Notebook362126

• Ziqi-Li/Spatio-temporal-Kriging-R

  r scripts for 3d kriging interpolation

  Language:R9

• mmaelicke/scikit-gstat

  Geostatistical variogram estimation expansion in the scipy style

  Language:Jupyter Notebook22352

• jlmaurer/geostats-matlab

  A MATLAB package for geostatistical data analysis, including variogram estimation and kriging

  Language:Matlab84

• scikit-learn/scikit-learn

  scikit-learn: machine learning in Python

  Language:Python59.7k25.3k

• q145492675/GMM-GaussianMixtureModel-matlab

  This routine is implemented in Matlab

  Language:Matlab42

• wrayzheng/gmm-em-clustering

  高斯混合模型（GMM 聚类）的 EM 算法实现。

  Language:Python18960