Name: Song Xiangyu
Type: User
Company: University of Chinese Academy of Sciences;China RailwayDesign Corporation
Bio: Xiangyu Song received the PhD degree from University of Chinese Academy of Sciences, China, in 2022. Currently, He works in China Railway Design Corporation.
Location: Tianjin
Song Xiangyu's Projects
Unsupervised Spatial-Spectral Feature Learning by 3-Dimensional Convolutional Autoencoder for Hyperspectral Classification
Bayesian Change-Point Detection and Time Series Decomposition
Demo of using aNNE similarity for DBSCAN.
Anomaly detection related books, papers, videos, and toolboxes
Code for the paper "Automatic Design of Convolutional Neural Network for Hyperspectral Image Classification"
A curated list of awesome anomaly detection resources
Awesome anomaly detection in medical images
Resources for independent developers to make money
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
HSI Band Selection
bloop is a fast code search engine written in Rust.
A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules
Categorized extended isolation forest tool
A CHRIS/Proba toolbox for SNAP
Clustering / Subspace Clustering Algorithms on MATLAB
isolation kernel
Code for the paper "Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification"
Differentiable architecture search for convolutional and recurrent networks
Source code for ``Deep Learning-Based Classification of Hyperspectral Data'' published at JSTAR
This is a code set for spectral-spatial hyperpsectral classifcation, including the EMAP, Gabor, LORSAL, LibSVM, MRF, and LBP methods.
Hyperspectral Image Classification
Extended Isolation Forest for Anomaly Detection
The code of the paper "Flexible Gabor-based Superpixel-level Unsupervised LDA for Hyperspectral Image Classification".
Gabor Feature Extraction
Geocomputation with Python: an open source book and online resource for getting started in this space
Matlab code for hyperspectral image classification based on JSaCR (IEEE GRSL, 2017)