Face Recognition using Independent Component Analysis

 
9783659193590: Face Recognition using Independent Component Analysis
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The Independent Component Analysis (ICA) plays very important role in blind source separation and has many more applications in pattern recognition. The ICA is new area for researchers in the last decade for face recognition. There is much more scope for research using ICA for face recognition with different methods of feature extractions and needs to be addressed. As the promising applications of ICA is feature extraction, where it extracts independent image bases which are not necessarily orthogonal and it is sensitive to high order statistics. In the task of face recognition, important information may be contained in the high order relationship among pixels. Independent Component Analysis (ICA) minimizes both second order and higher-order dependencies in the input data and attempts to find the basis along with the data when projected onto them are statistically independent. So ICA seems to be a promising face feature extraction method.

Biografía del autor:

Dr.Karande Kailash Jagannath has completed his Ph.D in Electronics and Telecommunication from S R T M University, Nanded, India. He has total17 Publications in International and National Journals and Conferences.He is member of ISTE and IETE. Currently he is working as Principal at SKN Sinhgad College of Engineering, Pandharpur, India.

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Karande, Kailash
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Buchbeschreibung LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Zustand: Neu. Neuware - The Independent Component Analysis (ICA) plays very important role in blind source separation and has many more applications in pattern recognition. The ICA is new area for researchers in the last decade for face recognition. There is much more scope for research using ICA for face recognition with different methods of feature extractions and needs to be addressed. As the promising applications of ICA is feature extraction, where it extracts independent image bases which are not necessarily orthogonal and it is sensitive to high order statistics. In the task of face recognition, important information may be contained in the high order relationship among pixels. Independent Component Analysis (ICA) minimizes both second order and higher-order dependencies in the input data and attempts to find the basis along with the data when projected onto them are statistically independent. So ICA seems to be a promising face feature extraction method. 136 pp. Englisch. Bestandsnummer des Verkäufers 9783659193590

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Buchbeschreibung LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Zustand: Neu. Neuware - The Independent Component Analysis (ICA) plays very important role in blind source separation and has many more applications in pattern recognition. The ICA is new area for researchers in the last decade for face recognition. There is much more scope for research using ICA for face recognition with different methods of feature extractions and needs to be addressed. As the promising applications of ICA is feature extraction, where it extracts independent image bases which are not necessarily orthogonal and it is sensitive to high order statistics. In the task of face recognition, important information may be contained in the high order relationship among pixels. Independent Component Analysis (ICA) minimizes both second order and higher-order dependencies in the input data and attempts to find the basis along with the data when projected onto them are statistically independent. So ICA seems to be a promising face feature extraction method. 136 pp. Englisch. Bestandsnummer des Verkäufers 9783659193590

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Kailash Karande; Sanjay Talbar
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Buchbeschreibung LAP Lambert Academic Publishing, Germany, 2012. Paperback. Zustand: New. Aufl. Language: English . Brand New Book ***** Print on Demand *****.The Independent Component Analysis (ICA) plays very important role in blind source separation and has many more applications in pattern recognition. The ICA is new area for researchers in the last decade for face recognition. There is much more scope for research using ICA for face recognition with different methods of feature extractions and needs to be addressed. As the promising applications of ICA is feature extraction, where it extracts independent image bases which are not necessarily orthogonal and it is sensitive to high order statistics. In the task of face recognition, important information may be contained in the high order relationship among pixels. Independent Component Analysis (ICA) minimizes both second order and higher-order dependencies in the input data and attempts to find the basis along with the data when projected onto them are statistically independent. So ICA seems to be a promising face feature extraction method. Bestandsnummer des Verkäufers AAV9783659193590

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Buchbeschreibung LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Neuware - The Independent Component Analysis (ICA) plays very important role in blind source separation and has many more applications in pattern recognition. The ICA is new area for researchers in the last decade for face recognition. There is much more scope for research using ICA for face recognition with different methods of feature extractions and needs to be addressed. As the promising applications of ICA is feature extraction, where it extracts independent image bases which are not necessarily orthogonal and it is sensitive to high order statistics. In the task of face recognition, important information may be contained in the high order relationship among pixels. Independent Component Analysis (ICA) minimizes both second order and higher-order dependencies in the input data and attempts to find the basis along with the data when projected onto them are statistically independent. So ICA seems to be a promising face feature extraction method. 136 pp. Englisch. Bestandsnummer des Verkäufers 9783659193590

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