Sinopsis
It has been observed that there are various factors that act as challenges in the process of image recognition like illumination, size, orientation, etc. In recent years, a new view-based approach to image recognition has been developed. In this book, we have analysed Principal Component Analysis, which is one of the most widely used algorithm for image recognition.The origins of PCA lie in multivariate data analysis; however, it has a wide range of other applications. PCA has been called having one of the most important results from applied linear algebra and perhaps its most common use is as the first step in trying to analyse large data sets. An experiment is described which is conducted to classify the images based on training data set of and observing the accuracy and time taken by the algorithm based on principal component analysis.
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Reseña del editor
It has been observed that there are various factors that act as challenges in the process of image recognition like illumination, size, orientation, etc. In recent years, a new view-based approach to image recognition has been developed. In this book, we have analysed Principal Component Analysis, which is one of the most widely used algorithm for image recognition.The origins of PCA lie in multivariate data analysis; however, it has a wide range of other applications. PCA has been called having one of the most important results from applied linear algebra and perhaps its most common use is as the first step in trying to analyse large data sets. An experiment is described which is conducted to classify the images based on training data set of and observing the accuracy and time taken by the algorithm based on principal component analysis.
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Principal Component Analysis
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LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200436142
ISBN 13: 9786200436146
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -It has been observed that there are various factors that act as challenges in the process of image recognition like illumination, size, orientation, etc. In recent years, a new view-based approach to image recognition has been developed. In this book, we have analysed Principal Component Analysis, which is one of the most widely used algorithm for image recognition.The origins of PCA lie in multivariate data analysis; however, it has a wide range of other applications. PCA has been called having one of the most important results from applied linear algebra and perhaps its most common use is as the first step in trying to analyse large data sets. An experiment is described which is conducted to classify the images based on training data set of and observing the accuracy and time taken by the algorithm based on principal component analysis. 52 pp. Englisch. Nº de ref. del artículo: 9786200436146
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Principal Component Analysis: An Algorithm for Image Recognition
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Principal Component Analysis: An Algorithm for Image Recognition
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Principal Component Analysis: An Algorithm for Image Recognition
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Principal Component Analysis
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khanchandani KhushiProf. Khushi Khanchandani, M.E (Computer Engineering), has been working in K. J. Somaiya College of Engineering, one of the most reputed Engineering colleges in Mumbai. She has a teaching experience of 12+ years fo. Nº de ref. del artículo: 385891578
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Principal Component Analysis
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -It has been observed that there are various factors that act as challenges in the process of image recognition like illumination, size, orientation, etc. In recent years, a new view-based approach to image recognition has been developed. In this book, we have analysed Principal Component Analysis, which is one of the most widely used algorithm for image recognition.The origins of PCA lie in multivariate data analysis; however, it has a wide range of other applications. PCA has been called having one of the most important results from applied linear algebra and perhaps its most common use is as the first step in trying to analyse large data sets. An experiment is described which is conducted to classify the images based on training data set of and observing the accuracy and time taken by the algorithm based on principal component analysis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Nº de ref. del artículo: 9786200436146
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Principal Component Analysis : An Algorithm for Image Recognition
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ISBN 10: 6200436142
ISBN 13: 9786200436146
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It has been observed that there are various factors that act as challenges in the process of image recognition like illumination, size, orientation, etc. In recent years, a new view-based approach to image recognition has been developed. In this book, we have analysed Principal Component Analysis, which is one of the most widely used algorithm for image recognition.The origins of PCA lie in multivariate data analysis; however, it has a wide range of other applications. PCA has been called having one of the most important results from applied linear algebra and perhaps its most common use is as the first step in trying to analyse large data sets. An experiment is described which is conducted to classify the images based on training data set of and observing the accuracy and time taken by the algorithm based on principal component analysis. Nº de ref. del artículo: 9786200436146
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Principal Component Analysis | An Algorithm for Image Recognition
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ISBN 10: 6200436142
ISBN 13: 9786200436146
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Taschenbuch. Condición: Neu. Principal Component Analysis | An Algorithm for Image Recognition | Khushi Khanchandani | Taschenbuch | 52 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200436146 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 117597216
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