Heterogeneous Domain Adaptation and Classification by Exploiting the Correlation Subspace

We present a novel domain adaptation approach for solving cross-domain pattern recognition problems, i.e., the data or features to be processed and recognized are collected from different domains of interest. Inspired by canonical correlation analysis (CCA), we utilize the derived correlation subspa...

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Veröffentlicht in:	IEEE transactions on image processing 2014-05, Vol.23 (5), p.2009-2018
Hauptverfasser:	Yeh, Yi-Ren, Huang, Chun-Hao, Wang, Yu-Chiang Frank
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Adaptation models Applied sciences Classification Correlation Correlation analysis Data models Detection, estimation, filtering, equalization, prediction Exact sciences and technology Feature recognition Handwriting recognition Image processing Information, signal and communications theory Kernel Pattern recognition Recognition Signal and communications theory Signal processing Signal representation. Spectral analysis Signal, noise Subspaces Support vector machines Telecommunications and information theory Training Vectors
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