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Danfeng Hong, Lianru Gao, Jing Yao, Naoto Yokoya, Jocelyn Chanussot, Uta Heiden, Bing Zhang. Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyper…
A repository for methods by and implemented by the authors' that were used in the paper: Blind Hyperspectral Unmixing using Autoencoders: A Critical Comparison
Python, Tensorflow Code for the conference paper -Convolutional Autoencoder for Blind Hyperspectral Image Unmixing
Spectral unmixing and classification (supervised, unsupervised) for Hyperspectral images (HSIs)
We build a challenging cloud detection dataset called AIR-CD, with higher spatial resolution and more representative landcover types.
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Updated Jan 28, 2021
Cloud masking for Landsat-8 & Sentinel-2
Here is an implementation of DeepLabv3+ in PyTorch(1.7). It supports many backbones and datasets.
The example project of inferencing Semantic Segementation using Core ML
deep learning for image processing including classification and object-detection etc.
Binary and Categorical Focal loss implementation in Keras.
Research Project Unit EGH400-1 (QUT)
Binary and Categorical Focal loss implementation in Keras.
Keras implementation of Representation Learning with Contrastive Predictive Coding
Keras implementation of Representation Learning with Contrastive Predictive Coding for images
Implements the ideas presented in https://arxiv.org/pdf/2004.11362v1.pdf by Khosla et al.
https://github.com/wenhwu/awesome-remote-sensing-change-detection
温州大学《机器学习》课程资料（代码、课件等）
Official PyTorch implementation of SegFormer
A simple Python script showing how the backpropagation algorithm works.
I will be implementing convolutional autoencoder on Indian pines dataset and will try and keep some noise in the unlabelled batches
UnDIP: Hyperspectral Unmixing Using Deep Image Prior
Hyperspectral Unmixing via Dual Attention Convolutional Neural Networks | 基于双注意力卷积神经网络的高光谱图像解混
This repo contains the 3D implementation of the commonly used attention mechanism for imaging.
Complete code for linear and non-linear unmixing Hyperspectral images in Python.
Code for the experiments on the Samson Dataset as presented in the paper: Hyperspectral Unmixing Using a Neural Network Autoencoder (Palsson et al. 2018)
Brief Introduction to Hyperspectral Image Analysis - Jupyter Notebook