Design and Analysis of Statistical Methods on Face Recognition - Akheel, T. Syed
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Face is an important biometric feature for personal identification. Human beings easily detect and identify faces in a scene but it is very challenging for an automated system to achieve such objectives. Dimensionality reduction has been a key problem in Face Recognition. Independent Component Analysis (ICA) is a recent approach for dimensionality reduction. Locality Preserving Projections (LPP) and linear collaborative discriminant regression methods are also a recently proposed new methods in pattern recognition for feature extraction and dimension reduction.

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Produktbeschreibung
Face is an important biometric feature for personal identification. Human beings easily detect and identify faces in a scene but it is very challenging for an automated system to achieve such objectives. Dimensionality reduction has been a key problem in Face Recognition. Independent Component Analysis (ICA) is a recent approach for dimensionality reduction. Locality Preserving Projections (LPP) and linear collaborative discriminant regression methods are also a recently proposed new methods in pattern recognition for feature extraction and dimension reduction.
Autorenporträt
Dr. T. Syed Akheel is a Professor inthe ECE Department at Dr. K.V. Subba Reddy Institute of Technology, Kurnool,Andhra Pradesh, serving since June 2018. He has previously held key roles,including Dean of Academics and Vice Principal. Presently he is working on deeplearning methods for real time applications.