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Kernel Principal Component Analysis and its Applications in Face
  Recognition and Active Shape Models
v1v2v3 (latest)

Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models

15 July 2012
Quan Wang
    CVBM
ArXiv (abs)PDFHTML

Papers citing "Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models"

14 / 14 papers shown
Generative Flexible Latent Structure Regression (GFLSR) model
Generative Flexible Latent Structure Regression (GFLSR) model
Clara Grazian
Qian Jin
Pierre Lafaye De Micheaux
105
0
0
06 Aug 2025
Machine Learning in Aerodynamic Shape Optimization
Machine Learning in Aerodynamic Shape OptimizationProgress in Aerospace Sciences (Prog. Aerosp. Sci.), 2022
Ji-chao Li
Xiaosong Du
J. Martins
AI4CE
398
297
0
15 Feb 2022
Probabilistic Bearing Fault Diagnosis Using Gaussian Process with
  Tailored Feature Extraction
Probabilistic Bearing Fault Diagnosis Using Gaussian Process with Tailored Feature Extraction
Mingxuan Liang
Kai Zhou
AI4CE
155
23
0
19 Sep 2021
Probabilistic combination of eigenlungs-based classifiers for COVID-19
  diagnosis in chest CT images
Probabilistic combination of eigenlungs-based classifiers for COVID-19 diagnosis in chest CT images
J. E. Arco
A. Ortiz
Javier Ramírez
Francisco J. Martínez-Murcia
Yudong Zhang
J. Broncano
M. '. Berbís
J. Royuela-del-Val
Antonio Luna
Juan M Gorriz
172
3
0
04 Mar 2021
A kernel Principal Component Analysis (kPCA) digest with a new backward
  mapping (pre-image reconstruction) strategy
A kernel Principal Component Analysis (kPCA) digest with a new backward mapping (pre-image reconstruction) strategy
Alberto García-González
A. Huerta
S. Zlotnik
Pedro Díez
145
18
0
07 Jan 2020
Modeling and Optimization with Gaussian Processes in Reduced Eigenbases
  -- Extended Version
Modeling and Optimization with Gaussian Processes in Reduced Eigenbases -- Extended VersionStructural And Multidisciplinary Optimization (SMO), 2019
David Gaudrie
Rodolphe Le Riche
Victor Picheny
B. Enaux
V. Herbert
288
23
0
29 Aug 2019
Extending classical surrogate modelling to high-dimensions through
  supervised dimensionality reduction: a data-driven approach
Extending classical surrogate modelling to high-dimensions through supervised dimensionality reduction: a data-driven approach
C. Lataniotis
S. Marelli
Bruno Sudret
323
80
0
15 Dec 2018
Taming VAEs
Taming VAEs
Danilo Jimenez Rezende
Fabio Viola
DRLCML
322
193
0
01 Oct 2018
Labelling as an unsupervised learning problem
Labelling as an unsupervised learning problem
Terry Lyons
Imanol Perez Arribas
74
1
0
10 May 2018
Empirical Evaluation of Kernel PCA Approximation Methods in
  Classification Tasks
Empirical Evaluation of Kernel PCA Approximation Methods in Classification Tasks
Deena P. Francis
K. Raimond
97
3
0
12 Dec 2017
Model-free Nonconvex Matrix Completion: Local Minima Analysis and
  Applications in Memory-efficient Kernel PCA
Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA
Ji Chen
Xiaodong Li
336
29
0
06 Nov 2017
Learning Discriminative Features using Encoder-Decoder type Deep Neural
  Nets
Learning Discriminative Features using Encoder-Decoder type Deep Neural Nets
Vishwajeet Singh
K. Kumar
K. Eswaran
AI4CE
111
0
0
22 Mar 2016
Feature Learning by Multidimensional Scaling and its Applications in
  Object Recognition
Feature Learning by Multidimensional Scaling and its Applications in Object Recognition
Quan Wang
K. Boyer
92
23
0
14 Jun 2013
Diffusion map for clustering fMRI spatial maps extracted by independent
  component analysis
Diffusion map for clustering fMRI spatial maps extracted by independent component analysisInternational Workshop on Machine Learning for Signal Processing (MLSP), 2013
T. Sipola
Fengyu Cong
T. Ristaniemi
Vinoo Alluri
P. Toiviainen
E. Brattico
Asoke K. Nandi
397
9
0
06 Jun 2013
1
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