Feature fusion using Discriminant Correlation Analysis (DCA)

버전 1.0.1 (3.82 KB) 작성자: Mohammad Haghighat

https://github.com/mhaghighat/dcaFuse

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업데이트 날짜: 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.
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.

인용 양식

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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Help Center 및 MATLAB Answers에서 Dimensionality Reduction and Feature Extraction에 대해 자세히 알아보기

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

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dcaFuse

GitHub 디폴트 브랜치를 사용하는 버전은 다운로드할 수 없음

버전	게시됨	릴리스 정보
1.0.1	2020/1/31	Updated the README
1.0.0.0	2017/2/16	Added the references Added the references

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릴리스 정보

1.0.1

2020/1/31

Updated the README

1.0.0.0

2017/2/16

Added the references

이 GitHub 애드온의 문제를 보거나 보고하려면 GitHub 리포지토리로 가십시오.

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} }