Project Page of Combining 3D Morphable Models: A Large scale Face-and-Head Model - [CVPR 2019]

A MATLAB toolbox for classifier: Version 1.0.7

MATLAB implementation for Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and k-Means Clustering.

Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of clas…

Group ICA/IVA software (MATLAB)

Head-related Transfer Function Customization Process through Slider using PCA and SH in Matlab

SJTU CS386 Digital Image Processing

Source code for the 2019 IEEE TIFS paper "PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition"

Federated Principal Component Analysis Revisited!

基于PCA的人脸识别

Fusion ICA Toolbox (MATLAB)

Streaming, Memory-Limited, r-truncated SVD Revisited!

Implemented and evaluated four basic face recognition algorithms: Eigenfaces, Fisherfaces, Support Vector Machine (SVM), and Sparse Representation-based Classification (SRC) on YaleB dataset

Multi-Sensor Image (infrared and visible) Fusion using deep learning framework, Principal Component Analysis, Discrete Wavelet Transform

Source code for the 2019 IEEE CIVEMSA paper "Touchless palmprint and finger texture recognition: A Deep Learning fusion approach"

Unsupervised Change Detection Algorithm using PCA and K-Means Clustering

Demonstration of FusionNet for touchless palmprint and finger texture recognition. Based on the source code for the 2019 IEEE CIVEMSA paper "Touchless palmprint and finger texture recognition: A Deep Learning fusion approach"

HAPOD - Hierarchical Approximate Proper Orthogonal Decomposition

Official implementation of PAS-MEF: Multi-exposure image fusion based on principal component analysis, adaptive well-exposedness and saliency map (IEEE ICASSP 2022)

This system can match human face over a webcam against the pictures stored in a database, primarily by matching facial features such as face, nose and eyes.