کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
408083 | 678242 | 2011 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Exponential locality preserving projections for small sample size problem
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Locality preserving projections (LPP) is a widely used manifold reduced dimensionality technique. However, it suffers from two problems: (1) small sample size problem and (2) the performance is sensitive to the neighborhood size k. In order to address these problems, we propose an exponential locality preserving projections (ELPP) by introducing the matrix exponential in this paper. ELPP avoids the singular of the matrices and obtains more valuable information for LPP. The experiments are conducted on three public face databases, ORL, Yale and Georgia Tech. The results show that the performances of ELPP is better than those of LPP and the state-of-the-art LPP Improved1.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 3654–3662
Journal: Neurocomputing - Volume 74, Issue 17, October 2011, Pages 3654–3662
نویسندگان
Su-Jing Wang, Hui-Ling Chen, Xu-Jun Peng, Chun-Guang Zhou,