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Face Recognition:Semisupervised Classification, Subspace Projection and Evaluation Methods

Face Recognition:Semisupervised Classification, Subspace Projection and Evaluation Methods

Face Recognition:Semisupervised Classification, Subspace Projection and Evaluation Methods Hardback - 2016

by S. Ramakrishnan (Editor)

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Hardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; Pattern recognition has gained significant attention due to the rapid explosion of internet- and mobile-based applications. Among the various pattern recognition applications, face recognition is always being the center of attraction. W
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Details

  • Title Face Recognition:Semisupervised Classification, Subspace Projection and Evaluation Methods
  • Author S. Ramakrishnan (Editor)
  • Binding Hardback
  • Edition U.S.EDITION
  • Condition New
  • Pages 104
  • Volumes 1
  • Language ENG
  • Publisher Intechopen
  • Publication date 2016-07-06
  • Bookseller's Inventory # ria9789535124214_inp
  • ISBN 9789535124214 / 9535124218
  • Weight 0.82 lbs (0.37 kg)
  • Dimensions 9.61 x 6.69 x 0.31 in (24.41 x 16.99 x 0.79 cm)
  • Category Computers - Computer Security
  • Quantity available 271

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Reader reviews for Face Recognition:Semisupervised Classification, Subspace Projection and Evaluation Methods

From the publisher

Pattern recognition has gained significant attention due to the rapid explosion of internet- and mobile-based applications. Among the various pattern recognition applications, face recognition is always being the center of attraction. With so much of unlabeled face images being captured and made available on internet (particularly on social media), conventional supervised means of classifying face images become challenging. This clearly warrants for semi-supervised classification and subspace projection. Another important concern in face recognition system is the proper and stringent evaluation of its capability. This book is edited keeping all these factors in mind. This book is composed of five chapters covering introduction, overview, semi-supervised classification, subspace projection, and evaluation techniques.
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