Compute the optimal number of bands essential for dimensionaity reduction

Demo of using aNNE similarity for DBSCAN.

matlab pfile decrypt to mfile

Clustering / Subspace Clustering Algorithms on MATLAB

Anomaly detection related books, papers, videos, and toolboxes

Source code of "A Single Model CNN for Hyperspectral Image Denoising"

For hyperspectral images (HSIs), it is a challenging task to select discriminative bands due to the lack of labeled samples and complex noise. In this article, we present a novel local-view-assiste…

Outlier/anomaly detection for Ruby using Isolation Forest

(Python, R, C++) Extended Isolation Forest, SCiForest, Fair-Cut Forest, with some additions (outlier detection + NA imputation + similarity)

Categorized extended isolation forest tool

Python - 100天从新手到大师

scikit-learn: machine learning in Python

📖 [译] scikit-learn（sklearn） 中文文档

Extended Isolation Forest for Anomaly Detection

code for TIP 2019 paper: Hyperspectral Image Super-Resolution via Subspace-Based Low Tensor Multi-Rank Regularization

implementation of papers attempting unsupervised band selection.

Python code of Hilbert-Schmidt Independence Criterion

Codes for 2020 IGARSS NEURAL NETWORK PRUNING FOR HYPERSPECTRAL IMAGE BAND SELECTION

手写实现李航《统计学习方法》书中全部算法

KPCA for dimensionality reduction, feature extraction , fault detection, and fault diagnosis

A list of hyperspectral image denoising resources collected by Yongsen Zhao and Junjun Jiang.

This Toolbox includes Hyperspectral Feature Extraction Techniques including Unsupervised, Supervised, and Deep Feature Extraction

Viewer for hyperspectral Numpy cubes and (2d/3d/4d)-tensors. (GPLv2)

Dimensionality reduction and classification of hyperspectral image based on SuperPCA (IEEE TGRS, 2018)