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JMLR
2006
104views more  JMLR 2006»
15 years 4 months ago
Learning Image Components for Object Recognition
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
Michael W. Spratling
IPAS
2010
15 years 2 months ago
An unsupervised learning approach for facial expression recognition using semi-definite programming and generalized principal co
In this paper, we consider facial expression recognition using an unsupervised learning framework. Specifically, given a data set composed of a number of facial images of the same...
Behnood Gholami, Wassim M. Haddad, Allen Tannenbau...
ICPR
2006
IEEE
16 years 5 months ago
Multilinear Principal Component Analysis of Tensor Objects for Recognition
In this paper, a multilinear formulation of the popular Principal Component Analysis (PCA) is proposed, named as multilinear PCA (MPCA), where the input can be not only vectors, b...
Anastasios N. Venetsanopoulos, Haiping Lu, Konstan...
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ICPR
2004
IEEE
16 years 5 months ago
Principal Component Analysis for Online Handwritten Character Recognition
In this paper, Principal Component Analysis (PCA) is applied to the problem of Online Handwritten Character Recognition in the Tamil script. The input is a temporally ordered sequ...
A. G. Ramakrishnan, Sriganesh Madhvanath, V. Deepu
INTERSPEECH
2010
14 years 11 months ago
Improved language recognition using mixture components statistics
One successful approach to language recognition is to focus on the most discriminative high level features of languages, such as phones and words. In this paper, we applied a simi...
Abualsoud Hanani, Michael J. Carey 0002, Martin J....