Feature fusion using Discriminant Correlation Analysis (DCA)

Version 1.0.1 (3,82 KB) von Mohammad Haghighat

https://github.com/mhaghighat/dcaFuse

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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.
DCAFUSE applies feature level fusion using a method based on Discriminant Correlation Analysis (DCA). It gets the train and test data matrices from two modalities X and Y, along with their corresponding class labels and consolidates them into a single feature set Z.

Details can be found in:

M. Haghighat, M. Abdel-Mottaleb, W. Alhalabi, "Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition," IEEE Transactions on Information Forensics and Security, vol. 11, no. 9, pp. 1984-1996, Sept. 2016.
http://dx.doi.org/10.1109/TIFS.2016.2569061

and

M. Haghighat, M. Abdel-Mottaleb W. Alhalabi, "Discriminant Correlation Analysis for Feature Level Fusion with application to multimodal biometrics," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, pp. 1866-1870.
http://dx.doi.org/10.1109/ICASSP.2016.7472000

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

Zitieren als

Haghighat, Mohammad, et al. “Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition.” IEEE Transactions on Information Forensics and Security, vol. 11, no. 9, Institute of Electrical and Electronics Engineers (IEEE), Sept. 2016, pp. 1984–96, doi:10.1109/tifs.2016.2569061.

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Inspiriert von: Dimensionality Reduction using Generalized Discriminant Analysis (GDA), Feature fusion using Canonical Correlation Analysis (CCA)

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dcaFuse

Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden

Version	Veröffentlicht	Versionshinweise
1.0.1	31 Jan 2020	Updated the README
1.0.0.0	16 Feb 2017	Added the references Added the references

Version

Veröffentlicht

Versionshinweise

1.0.1

31 Jan 2020

Updated the README

1.0.0.0

16 Feb 2017

Added the references

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.

MLA	Haghighat, Mohammad, et al. “Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition.” IEEE Transactions on Information Forensics and Security, vol. 11, no. 9, Institute of Electrical and Electronics Engineers (IEEE), Sept. 2016, pp. 1984–96, doi:10.1109/tifs.2016.2569061.
APA	Haghighat, M., Abdel-Mottaleb, M., & Alhalabi, W. (2016). Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition. IEEE Transactions on Information Forensics and Security, 11(9), 1984–1996. Institute of Electrical and Electronics Engineers (IEEE). Retrieved from https://doi.org/10.1109%2Ftifs.2016.2569061
BibTeX	@article{Haghighat_2016, doi = {10.1109/tifs.2016.2569061}, url = {https://doi.org/10.1109%2Ftifs.2016.2569061}, year = 2016, month = {sep}, publisher = {Institute of Electrical and Electronics Engineers ({IEEE})}, volume = {11}, number = {9}, pages = {1984--1996}, author = {Mohammad Haghighat and Mohamed Abdel-Mottaleb and Wadee Alhalabi}, title = {Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition}, journal = {{IEEE} Transactions on Information Forensics and Security} }