Iterative Dynamic Generic Learning, TNNLS'2020

MATLAB implementation of Iterative Dynamic Generic Learning (IDGL) [1]

If you find this software useful and use it in your own work, please cite our paper:

[1] M. Pang, Y.-M. Cheung, Q. Shi, and M. Li, "Iterative dynamic generic learning for face recognition from a contaminated single-sample per person,” IEEE Transactions on Neural Networks and Learning Systems, 2020.

@article{pang2020iterative,

title={Iterative Dynamic Generic Learning for Face Recognition From a Contaminated Single-Sample Per Person},

author={Pang, Meng and Cheung, Yiu-Ming and Shi, Qiquan and Li, Mengke},

journal={IEEE Transactions on Neural Networks and Learning Systems},

year={2020},

publisher={IEEE}

}

The software is free for academic use, and shall not be used, rewritten, or adapted as the basis of a commercial product without first obtaining permission from the authors. The authors make no representations about the suitability of this software for any purpose. It is provided "as is" without express or implied warranty.