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Config files for my GitHub profile.
Band-Adaptive Spectral-Spatial Feature Learning Deep Neural Network for Hyperspectral Image Classification
This project implements blockchain applications for climate action and accounting, including emissions calculations, carbon trading, and validation of climate claims. It is part of the Linux Foundation's Hyperledger Climate Action and Accounting SIG.
Making carbon footprint data available to everyone.
Calculate your carbon footprint 🏭👣 from food, transport, purchases, fashion, electricity and digital activities like streaming, NFT or blockchain.
Reducing Global Carbon Footprint based on Multi-Agent Reinforcement Learning - School of AI Fellowship Research
The add-on "Carbonalyser" allows to visualize the electricity consumption and greenhouse gases (GHG) emissions that your Internet browsing leads to.
Track and predict the energy consumption and carbon footprint of training deep learning models.
Beginning Scene Kit Tutorial [RayWenderlich Tutorial]
Classification of the Hyperspectral Image Indian Pines with Convolutional Neural Network
Data on CO2 and greenhouse gas emissions by Our World in Data
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.
Documentation for GitHub Copilot
MSc Research project (6 months). Data Assimilation using Deep Learning (AEs). Imperial College Machine Learning MSc 2018-19
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
Hyperspectral image classification by exploring deep tensor facorization, published in IGARSS 2018.
Classification of Hyperspectral Satellite Image Using Deep Convolutional Neural Networks
This is a code set for spectral-spatial hyperpsectral classifcation, including the EMAP, Gabor, LORSAL, LibSVM, MRF, and LBP methods.
PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
Our final class project. Hyperspectral image classification.
Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series" (AAAI 2021)
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".
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Hyperspectral image classification with varies image processing and machine learning methods.
Hyperspectral image classification
Deep Learning for Land-cover Classification in Hyperspectral Images.
This repo contains an illustration of the use of kernel support vector machine for hyperspectral image classifiication as well as a comparison with least sqaure methods.
This is my Graduate Project on hyperspectral image classification.
This work contains KNN classification of Hyperspectral Satellite Images using the given groundtruth and finding success rate of the method. You can download the hypersectral images using the link below :http://www.ehu.eus/ccwintco/index.php?title=Hyperspectral_Remote_Sensing_Scenes&redirect=no#Pavia_University_scene
Matlab code for our JARS18 paper "Spectral and spatial classification of hyperspectral image based on random multi-graphs"
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.