Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

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 ...

Python is a general-purpose programming language and is one of the most popular languages because of its versatility, ease of use, libraries, and active community. Given its widespread adoption, it is ...

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 ...

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 ...

Principal Component Analysis (CA) is a popular technique with many applications. Recent randomized PCA algorithms scale to large datasets but face a bottleneck when the number of features is also ...

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 ...