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autoencodertestingenvironment

Experimental and testing environment for autoencoders

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

dive_into_deep_learning

✔️李沐 【动手学深度学习】课程学习笔记：使用pycharm编程，基于pytorch框架实现。

exercise

exercise for nndl

hu_autoencoders

A repository for methods by and implemented by the authors' that were used in the paper: Blind Hyperspectral Unmixing using Autoencoders: A Critical Comparison

huihua520

Config files for my GitHub profile.

hyperspecae

Code for the experiments on the Samson Dataset as presented in the paper: Hyperspectral Unmixing Using a Neural Network Autoencoder (Palsson et al. 2018)

hyperspectral

This repository contains several hyperspectral image analysis algorithms, including unmixing, registration and fusion.

hyperspectral-unmixing

machine_learning_code_implementation

Mathematical derivation and pure Python code implementation of machine learning algorithms.

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

nnls-fcls-gpu

GPU Implementation of Large-Scale Abundance Estimation with Constraint Linear Spectral Mixture Model for Hyperspectral Unmixing

robust-unmixing-plmm

A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images

spectrai

spectrai: a deep learning framework for spectral data

spice

Sparsity Promoting Iterated Constrained Endmembers

stacked-autoencoder-pytorch

Stacked denoising convolutional autoencoder written in Pytorch for some experiments.

udas

Unsupervised spectral unmixing through an untied denoising autoencoder with sparsity (uDAS)

unmixing_spectral_variability

A complete toolbox for spectral unmixing with spectral variability

vca

Vertex Component Analysis in Python