<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/12509" mdate="2008-12-25 00:00:00"> <author>Mehdi Ghayoumi</author> <title>New Adaptive Linear Discriminante Analysis for Face Recognition with SVM</title> <pages>4283 - 4286</pages> <year>2008</year> <volume>2</volume> <number>12</number> <journal>International Journal of Computer and Information Engineering</journal> <ee>https://publications.waset.org/pdf/12509</ee> <url>https://publications.waset.org/vol/24</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.</abstract> <index>Open Science Index 24, 2008</index> </article>