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» Applying VC-dimension Analysis To Object Recognition
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SSIAI
2000
IEEE
14 years 2 months ago
Multi-Level Shape Recognition Based on Wavelet-Transform Modulus Maxima
In this paper we propose a new approach to shape recognition based on the wavelet transform modulus maxima. And apply it to the problem of content-based indexing and retrieval of ...
Faouzi Alaya Cheikh, Azhar Quddus, Moncef Gabbouj
ICASSP
2010
IEEE
13 years 10 months ago
Fishervioce: A discriminant subspace framework for speaker recognition
We propose a new framework for speaker recognition, referred as Fishervoice. It includes the design of a feature representation known as the structured score vector (SSV), which r...
Zhifeng Li, Weiwu Jiang, Helen M. Meng
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 11 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
CVPR
2009
IEEE
14 years 4 months ago
Symmetric two dimensional linear discriminant analysis (2DLDA)
Linear discriminant analysis (LDA) has been successfully applied into computer vision and pattern recognition for effective feature extraction. High-dimensional objects such as im...
Dijun Luo, Chris H. Q. Ding, Heng Huang
PAMI
2007
217views more  PAMI 2007»
13 years 9 months ago
Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations
—We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and li...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla