ywg0212

Ph.D

Nanjing Agricultural University

Pinned Repositories

agoro-field-boundary-detector
Detect field boundaries using satellite imagery.
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An-Introduction-to-Statistical-Learning
This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning in python.
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AtmosphericCorrection
6s模型大气校正python版本，支持GF1、2,Landsat-8,Sentinel-2等影像
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BayesianOptimization
A Python implementation of global optimization with gaussian processes.
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catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
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causalml
Uplift modeling and causal inference with machine learning algorithms
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custom-scripts
A repository of custom scripts to be used with Sentinel Hub
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EarthML
Tools for working with machine learning in earth science
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GEE_STARFM_FUSION
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tf2_course
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
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ywg0212's Repositories

ywg0212/agoro-field-boundary-detector
Detect field boundaries using satellite imagery.
Language:Jupyter Notebook0 0 00
ywg0212/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Language:C0 0 00
ywg0212/causalml
Uplift modeling and causal inference with machine learning algorithms
Language:Python0 0 00
ywg0212/custom-scripts
A repository of custom scripts to be used with Sentinel Hub
Language:JavaScript0 0 00
ywg0212/DL4ES
ywg0212/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
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ywg0212/ee_BioNet
The Google Earth Engine implementation of the BioNet algorithm to estimate biophysical parameters along with their uncertainties.
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ywg0212/eemont
A python package that extends Google Earth Engine.
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ywg0212/field-delineation
Field delineation with Sentinel-2 data from Sentinel-Hub and a ResUnet-a architecture.
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ywg0212/GEE-Image-Fusion
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ywg0212/gee_s1_ard
Creates an analysis ready sentinel-1 SAR image collection in Google Earth Engine by applying additional border noise correction, speckle filtering and radiometric terrain normalization.
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ywg0212/GEET
Google Earth Engine Toolbox - Library to write small EE apps or big/complex apps with a lot less code.
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ywg0212/GlobalC
A topdown and bottom up approach for global C cycle
ywg0212/GlobalSolarPosition
Global computation of the solar position at a given time in Google Earth Engine
ywg0212/iMetaPlot
iMeta teaches you to plot
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ywg0212/isce2
InSAR Scientific Computing Environment version 2
ywg0212/isofit
Imaging Spectrometer Optimal FITting
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ywg0212/LST-downscaling-to-10m-GEE
This code repository is an attachment for the article in Remote Sensing: Onačillová, K.; Gallay, M.; Paluba, D.; Péliová, A.; Tokarčík, O.; Laubertová, D. Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment. https://doi.org/10.3390/rs14164076
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ywg0212/mgwr
Multiscale Geographically Weighted Regression (MGWR)
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ywg0212/MintPy
Miami InSAR time-series software in Python
ywg0212/MintPy-tutorial
Tutorials in Jupyter Notebook for MintPy
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ywg0212/mlens
ML-Ensemble – high performance ensemble learning
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ywg0212/NRT-MONITOR
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ywg0212/REddyProc
Processing data from micrometeorological Eddy-Covariance systems
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ywg0212/satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
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ywg0212/Sentinel-2_GPP
This is the code repository for the manuscript: "On the potential of Sentinel-2 for estimating Gross Primary Production" for further details see: https://ieeexplore.ieee.org/document/9715117
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ywg0212/sentinel2_crop_traits
Sentinel-2 Crop Trait Retrieval Using Physiological and Phenological Priors from Field Phenotyping (Graf et al., 2023, RSE)
Language:Python0 0
ywg0212/smogn
Synthetic Minority Over-Sampling Technique for Regression
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ywg0212/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
ywg0212/WZU-machine-learning-course
温州大学《机器学习》课程资料（代码、课件等）