Two-dimensional PCA: a new approach to appearance-based face representation and recognition.
about
Fusion tensor subspace transformation frameworkMapping and manipulating facial expression2.5D multi-view gait recognition based on point cloud registration.False-positive reduction in mammography using multiscale spatial Weber law descriptor and support vector machines.Coupled parametric model for estimation of visual field tests based on OCT macular thickness maps, and vice versa, in glaucoma careNew robust face recognition methods based on linear regression.A multifaceted independent performance analysis of facial subspace recognition algorithms.Face recognition using sparse representation-based classification on k-nearest subspaceImproved minimum squared error algorithm with applications to face recognition.Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera NetworksWood recognition using image texture features.A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.Robust Generalized Low Rank Approximations of Matrices.Sorting algorithms for single-particle imaging experiments at X-ray free-electron lasers.Finger vein recognition based on (2D)² PCA and metric learning.Supervised Filter Learning for Representation Based Face Recognition.Palmprint Recognition Across Different DevicesCharacterizing Variability of Modular Brain Connectivity with Constrained Principal Component AnalysisAn efficient classification method based on principal component and sparse representation.A Statistical Texture Model of the Liver Based on Generalized N-Dimensional Principal Component Analysis (GND-PCA) and 3D Shape Normalization.Unsupervised 2D Dimensionality Reduction with Adaptive Structure Learning.Avoiding Optimal Mean ℓ2,1-Norm Maximization-Based Robust PCA for Reconstruction.Thresholded two-phase test sample representation for outlier rejection in biological recognition.Eigendetection of masses considering false positive reduction and breast density information.Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices.Is principal component analysis an effective tool to predict face attractiveness? A contribution based on real 3D faces of highly selected attractive women, scanned with stereophotogrammetry.Clinical risk prediction by exploring high-order feature correlations.A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVMShape component analysis: structure-preserving dimension reduction on biological shape spaces.Principal-component analysis of particle motion.Patch-Based Principal Component Analysis for Face Recognition.GPCA vs. PCA in recognition and 3-D localization of ultrasound reflectors.Two-Dimensional Whitening Reconstruction for Enhancing Robustness of Principal Component AnalysisLarge margin low rank tensor analysis.Classification of facial diagnosis gloss in Chinese medicine based on different algorithms.Maximum neighborhood margin discriminant projection for classification.Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis.Average gait differential image based human recognition.Converted-face identification: using synthesized images to replace original images for recognitionFace recognition method based on HOG and DMMA from single training sample
P2860
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P2860
Two-dimensional PCA: a new approach to appearance-based face representation and recognition.
description
2004 nî lūn-bûn
@nan
2004年の論文
@ja
2004年学术文章
@wuu
2004年学术文章
@zh
2004年学术文章
@zh-cn
2004年学术文章
@zh-hans
2004年学术文章
@zh-my
2004年学术文章
@zh-sg
2004年學術文章
@yue
2004年學術文章
@zh-hant
name
Two-dimensional PCA: a new app ...... epresentation and recognition.
@en
Two-dimensional PCA: a new app ...... epresentation and recognition.
@nl
type
label
Two-dimensional PCA: a new app ...... epresentation and recognition.
@en
Two-dimensional PCA: a new app ...... epresentation and recognition.
@nl
prefLabel
Two-dimensional PCA: a new app ...... epresentation and recognition.
@en
Two-dimensional PCA: a new app ...... epresentation and recognition.
@nl
P1476
Two-dimensional PCA: a new app ...... epresentation and recognition.
@en
P2093
Jing-yu Yang
P304
P356
10.1109/TPAMI.2004.1261097
P407
P577
2004-01-01T00:00:00Z