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Title: 2011 ieee papers on face recognition free down
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Created at: Monday 04th of March 2013 01:37:49 PM
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Title: Face Recognition using the Techniques Base on Principal Component Analysis PCA
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Posted By: Computer Science Clay
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Face Recognition using the Techniques Base on Principal Component Analysis (PCA)

several past few years, Face Recognition has become more significant. Although, other identification methods such as Fingerprints or Iris recognition are currently in use, face recognition has its own application.

Principal Component Analysis (PCA) has been variously used in pattern recognition applications, especially in face recognition field. In this seminars, several techniques based on standard PCA, Fisher Linear ....etc

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Title: free download ieee base papers 2013 cse
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Title: Face recognition using laplaction face at java
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The face recognition is a fairly controversial subject right now. A system such as this can recognize and track dangerous criminals and terrorists in a crowd, but some contend that it is an extreme invasion of privacy. The proponents of large-scale face recognition feel that it is a necessary evil to make our country safer. It could benefit the visually impaired and allow them to interact more easily with the environment. Also, a computer vision-based authentication system could be pu ....etc

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Title: ieee base papers 2013 for cse free download
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Title: Face Recognition using the Techniques Base on Principal Component Analysis PCA
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Posted By: computer science crazy
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During several past few years, Face Recognition has become more significant. Although, other identification methods such as Fingerprints or Iris recognition are currently in use, face recognition has its own application. Principal Component Analysis (PCA) has been variously used in pattern recognition applications, especially in face recognition field. In this seminars, several techniques based on standard PCA, Fisher Linear Discriminant (FLD), Face Specific Subspace (FSS) will be discussed. We will review the developed idea used in the 2D-PCA ....etc

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