Abstract: This paper presents a PCA (Principal Component Analysis) data dimensionality reduction algorithm based on OPNs (Ordered Pair of Normalized Real Numbers), referred to as OPNs-PCA. This ...

Abstract: Aiming at the problem that traditional clustering algorithms cannot adapt to spatiotemporal data mining, this paper proposes a new clustering algorithm PCA-Kmeans++. First, in order to ...

This project is an implementation of Principal Component Analysis (PCA) in Python. PCA is a technique for dimensionality reduction and data visualization that aims to find the most important ...

Implementing PCA (Principal Component Analysis) from scratch for Dimensionality Reduction which is Reducing the number of input variables for a predictive model ...

In this paper, the authors discuss some of the popular face recognition algorithms. Face recognition is widely used biometric technique at many places like international airports, gaming industries ...

ABSTRACT: Tracking and segmentation of moving objects are suffering from many problems including those caused by elimination changes, noise and shadows. A modified algorithm for the adaptive ...

ABSTRACT: In order to increase robustness of the AERS (Aero-engine Rotor System) and to solve the problem of lacking fault samples in fault diagnosis and the difficulty in identifying early weak fault ...