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Independent Component Analysis - an overview ...
jICA is an extension of the popular independent component analysis (ICA). Briefly, ICA is a technique for revealing hidden factors that underlie a set of observable data. ICA has been widely used to solve blind source separation problems (Fig. 16.3); these include, for example, the problem of deriving brain waves recorded using multiple sensors and the problem of removing interfering radio ...
A Robust Method for Nose Detection under Various ...
It depends on the local appearance and shape of nose region characterized by edge information. Independent Components Analysis (ICA) is used to learn the appearance of nose. We show experimentally that using edge information for characterizing appearance and shape outperforms using intensity information....
A Comparative Study of Blind Source Separation for ...
(2002) "Face recognition by independent component analysis." IEEE Transactions on neural networks 13(6): 1450-1464. [12] Migliorelli, Carolina, Joan F. Alonso, Sergio Romero, Miguel A. Mañanas, Rafał Nowak, and Antonio Russi.
 ISSN : 2454-9150 SVM and ANN-based Comparison of Face ...
Abstract— Face recognition is a very important component of human intelligence. For individual identity faces are rich in information. Since last few years, face recognition have been most important and successful applications of machine learning and computer security. The major method for face recognition consists of two steps....
Independent Component Analysis (ICA)
Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS. [Cited by 75] (6.72/year) BARTLETT, M.S., J.R. MOVELLAN and T.J. SEJNOWSKI, 2002. Face recognition by independent component analysis. Neural Networks, IEEE Transactions on. [Cited by 367] (59.51/year)...
CiteSeerX — Citation Query Independent component analysis ...
New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. ... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into ......
ICA for dummies – Arnaud Delorme
Independent Component Analysis is a signal processing method to separate independent sources linearly mixed in several sensors. For instance, when recording electroencephalograms (EEG) on the scalp, ICA can separate out artifacts embedded in the data (since they are usually independent of each other).
A FAST FIXED-POINT ALGORITHM FOR INDEPENDENT COMPONENT ...
The study of face recognition based on hybrid principal components analysis and independent component analysis Yanhong Zhou, Shukai Cao, Dong Wen, Huiyang Zhang and Liqiang Zhao 1 Sep 2011
Independent component analysis: an introduction: Trends in ...
Independent component analysis (ICA) is a method for automatically identifying the underlying factors in a given data set. This rapidly evolving technique is currently finding applications in analysis of biomedical signals (e.g. ERP, EEG, fMRI, optical imaging), and in models of visual receptive fields and separation of speech signals. This article illustrates these applications, and provides ...
US20080247608A1 - Method, System, Storage Medium, and Data ...
A method, system, computer-readable medium and data structure are provided for processing image data in connection with image recognition. A response of an image (FIG. 6 element 210 ) to a basis tensor can be determined after the image is applied thereto. The image response can be flattened (FIG. 6 element 220 ). A coefficient vector may be extracted from the image response (FIG.
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