کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
535090 870319 2009 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Enhanced supervised locally linear embedding
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Enhanced supervised locally linear embedding
چکیده انگلیسی

In this paper, a new nonlinear dimensionality reduction algorithm, called enhanced supervised locally linear embedding (ESLLE), is proposed. The ESLLE method attempts to make the interclass dissimilarity definitely larger than the intraclass dissimilarity in an effort to strengthen the discriminating power and generalization ability of embedded data representation. Simulation studies on artificial manifold data demonstrate that ESLLE can give better embedding results in dimensionality reduction and is more robust to noise in comparison with the original supervised LLE (SLLE). Experimental results on extended Yale face database B and CMU PIE face databases demonstrate that ESLLE obtains better performance on face recognition compared with other famous methods such as principal component analysis (PCA), locally linear embedding (LLE) as well as SLLE.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 30, Issue 13, 1 October 2009, Pages 1208–1218
نویسندگان
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