Local linear discriminant analysis framework using sample neighbors
The linear discriminant analysis (LDA) is a very popular linear feature extraction approach.
The algorithms of LDA usually perform well under the following two assumptions. The first …
The algorithms of LDA usually perform well under the following two assumptions. The first …
[PDF][PDF] A Survey: Linear and Nonlinear PCA Based Face Recognition Techniques.
Face recognition is considered to be one of the most reliable biometric, when security issues
are taken into concern. For this, feature extraction becomes a critical problem. Different …
are taken into concern. For this, feature extraction becomes a critical problem. Different …
Employing fisher discriminant analysis for Arabic text classification
D AbuZeina, FS Al-Anzi - Computers & Electrical Engineering, 2018 - Elsevier
Fisher's discriminant analysis; also called linear discriminant analysis (LDA), is a popular
dimensionality reduction technique that is widely used for features extraction. LDA aims at …
dimensionality reduction technique that is widely used for features extraction. LDA aims at …
Classification With the Matrix-Variate-t Distribution
GZ Thompson, R Maitra, WQ Meeker… - … of Computational and …, 2020 - Taylor & Francis
Matrix-variate distributions can intuitively model the dependence structure of matrix-valued
observations that arise in applications with multivariate time series, spatio-temporal, or …
observations that arise in applications with multivariate time series, spatio-temporal, or …
Quality monitoring in wire-arc additive manufacturing based on cooperative awareness of spectrum and vision
This paper presents a multi-source classification method based on cooperative awareness
method of spectrum, vision and electrical parameter for the quality monitoring in wire-arc …
method of spectrum, vision and electrical parameter for the quality monitoring in wire-arc …
Low-rank linear embedding for image recognition
Locality preserving projections (LPP) has been widely studied and extended in recent years,
because of its promising performance in feature extraction. In this paper, we propose a …
because of its promising performance in feature extraction. In this paper, we propose a …
Rapid and low-cost detection of moldy apple core based on an optical sensor system
L Li, Y Peng, Y Li, C Yang, K Chao - Postharvest Biology and Technology, 2020 - Elsevier
An optical sensor system for the detection of moldy apple core (Malus domestica Borkh.)
was developed. The cost-effective optical sensor has seven specific wavelengths centered …
was developed. The cost-effective optical sensor has seven specific wavelengths centered …
An efficient face recognition approach combining likelihood-based sufficient dimension reduction and LDA
A Benouareth - Multimedia Tools and Applications, 2021 - Springer
In this paper, an efficient approach is proposed for face recognition (FR) under pose and
illumination variations. It is based on combining likelihood-based sufficient dimension …
illumination variations. It is based on combining likelihood-based sufficient dimension …
A two-dimensional neighborhood preserving projection for appearance-based face recognition
This paper presents a two-dimensional Neighborhood Preserving Projection (2DNPP) for
appearance-based face representation and recognition. 2DNPP enables us to directly use a …
appearance-based face representation and recognition. 2DNPP enables us to directly use a …
Fractional fuzzy 2DLDA approach for pomegranate fruit grade classification
Y Gurubelli, M Ramanathan, P Ponnusamy - Computers and Electronics in …, 2019 - Elsevier
In this research work, the fractional fuzzy two-dimensional linear discriminant analysis
(FF2DLDA) an extension of fuzzy 2DLDA (F2DLDA) is proposed and applied to grade the …
(FF2DLDA) an extension of fuzzy 2DLDA (F2DLDA) is proposed and applied to grade the …