https://github.com/mhaghighat/ccaFuse

Feature fusion using Canonical Correlation Analysis (CCA)
https://github.com/mhaghighat/ccaFuse

Last synced: 22 days ago
JSON representation

Feature fusion using Canonical Correlation Analysis (CCA)

• Host: GitHub
• URL: https://github.com/mhaghighat/ccaFuse
• Owner: mhaghighat
• License: bsd-2-clause
• Created: 2015-12-30T18:32:43.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-01-31T18:14:49.000Z (over 4 years ago)
• Last Synced: 2024-02-12T23:48:58.429Z (4 months ago)
• Language: MATLAB
• Size: 3.91 KB
• Stars: 46
• Watchers: 2
• Forks: 19
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

Lists

• awesome-cbir-papers - Feature fusion using Canonical Correlation Analysis
• awesome-image-retrieval-papers - Feature fusion using Canonical Correlation Analysis

README

        
# Feature fusion using Canonical Correlation Analysis (CCA)

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

      	[email protected]

      	PLEASE CITE THE ABOVE PAPER IF YOU USE THIS CODE.

[![View Feature fusion using Canonical Correlation Analysis (CCA) on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://www.mathworks.com/matlabcentral/fileexchange/54681-feature-fusion-using-canonical-correlation-analysis-cca)