Feature fusion using Canonical Correlation Analysis (CCA)

バージョン 1.0.1 (3.02 KB) 作成者: Mohammad Haghighat

Feature level fusion using Canonical Correlation Analysis (CCA)

https://github.com/mhaghighat/ccaFuse

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更新 2020/1/31

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Feature fusion is the process of combining two feature vectors to obtain a single feature vector, which is more discriminative than any of the input feature vectors.
CCAFUSE applies feature level fusion using a method based on Canonical Correlation Analysis (CCA). It gets the train and test data matrices from two modalities X and Y, and consolidates them into a single feature set Z.

Details can be found in:

M. Haghighat, M. Abdel-Mottaleb, W. Alhalabi, "Fully Automatic Face Normalization and Single Sample Face Recognition in Unconstrained Environments," Expert Systems With Applications, vol. 47, pp. 23-34, April 2016. http://dx.doi.org/10.1016/j.eswa.2015.10.047

(C) Mohammad Haghighat, University of Miami
haghighat@ieee.org
PLEASE CITE THE ABOVE PAPER IF YOU USE THIS CODE.

引用

Haghighat, Mohammad, et al. “Fully Automatic Face Normalization and Single Sample Face Recognition in Unconstrained Environments.” Expert Systems with Applications, vol. 47, Elsevier BV, Apr. 2016, pp. 23–34, doi:10.1016/j.eswa.2015.10.047.

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ヒントを得たファイル: Dimensionality Reduction using Generalized Discriminant Analysis (GDA)

ヒントを与えたファイル: Feature fusion using Discriminant Correlation Analysis (DCA)

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ccaFuse

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バージョン	公開済み	リリースノート
1.0.1	2020/1/31	Updated the references
1.0.0.0	2016/5/12

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MLA	Haghighat, Mohammad, et al. “Fully Automatic Face Normalization and Single Sample Face Recognition in Unconstrained Environments.” Expert Systems with Applications, vol. 47, Elsevier BV, Apr. 2016, pp. 23–34, doi:10.1016/j.eswa.2015.10.047.
APA	Haghighat, M., Abdel-Mottaleb, M., & Alhalabi, W. (2016). Fully automatic face normalization and single sample face recognition in unconstrained environments. Expert Systems with Applications, 47, 23–34. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.eswa.2015.10.047
BibTeX	@article{Haghighat_2016, doi = {10.1016/j.eswa.2015.10.047}, url = {https://doi.org/10.1016%2Fj.eswa.2015.10.047}, year = 2016, month = {apr}, publisher = {Elsevier {BV}}, volume = {47}, pages = {23--34}, author = {Mohammad Haghighat and Mohamed Abdel-Mottaleb and Wadee Alhalabi}, title = {Fully automatic face normalization and single sample face recognition in unconstrained environments}, journal = {Expert Systems with Applications} }