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Image Recognition and Image Processing Techniques ...
Image Restoration, which refers to the estimation of a clean original image out of the corrupt image taken in order to get back the information lost. Independent Component Analysis, which ...
 Region-Based Representations for Face Recognition
Region-Based Representations for Face Recognition • 357 Fig. 1. A schematic of our dipole operator. The most important aspect of this operator is the decoupling of the distance between lobes (δ) from the width of the lobes (σ). neighboring image regions, we would be able to use sufficiently large edgelike DOG features. However,
RESEARCH ARTICLE An Investigation of Face Recognition ...
This aims to investigate the face recognition characteristics using widely adopted statistical approaches (i.e., Principal Component Analysis (PCA) and Independent Component Analysis (ICA)). This paper focus on Eigen faces approach for implementing the face recognition and detection on the images to compare the performance of PCA and ICA....
Three-dimensional computational holographic imaging and ...
We present computational holographic three-dimensional imaging and automated object recognition based on independent component analysis (ICA). Three-dimensional sensing of the scene is performed by computational holographic imaging of the objects using phase-shifting digital holography.
RFID and Face Recognition Based Security and Access ...
m) Jun-Ying Gan, Si-Bin He on Proceedings of the Eighth International Conference on Machine Learning and Cybernetics, proposed an improved 2DPCA algorithm for face recognition. on the basis of two-dimensional principal component analysis, an improved two-dimensional principal component analysis (I2DPCA) is presented for face recognition....
Face Recognition Using Incremental Principal Component ...
Keywords— IPCA-ICA, Principal component analysis (PCA), independent component analysis (ICA), principal non-Gaussian directions, image processing, blind source separation. I. INTRODUCTION A large number of face recognition techniques use face representations found by unsupervised statistical methods....
Learning Modewise Independent Components from Tensor Data ...
Independent component analysis (ICA) is a popular unsupervised learning method. This paper extends it to multilinear modewise ICA (MMICA) for tensors and explores two architectures in learning and recognition. MMICA models tensor data as mixtures generated from modewise source matrices that encode statistically independent information....
Multilinear Projection ( M-Mode Pseudo-InverseTensor )
“Multilinear Independent Components Analysis and Multilinear Projection Operator for Face Recognition”, M.A.O. Vasilescu, D. Terzopoulos, in Workshop on Tensor Decompositions and Applications, CIRM, Luminy, Marseille, France, August 2005. Multilinear (Tensor) Independent Component Analysis...
Independent component analysis - WikiMili, The Best ...
Independent component analysis (1st ed.). New York: John Wiley & Sons. ISBN 978-0-471-22131-9. ↑ Johan Himbergand Aapo Hyvärinen, Independent Component Analysis For Binary Data: An Experimental Study, Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2001), San Diego, California, 2001....
Allassonnière , Younes : A stochastic algorithm for ...
Independent component analysis in statistical shape models. SPIE Medical Image Analysis 375–383. Valpola Lappalainen, H. and Pajunen, P. (2000). Fast algorithms for Bayesian independent component analysis. In Proc. of the Second International Workshop on Independent Component Analysis and Blind Signal Separation, ICA 2000, Helsinki, Finland ......
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