Inspired from the working principle of human memory, we propose a new algorithm for storing HTM features detected from images. The resulting features from the training set require lower memory than existing HTM training set. The proposed features are tested in a face recognition problem using the benchmark AR dataset. The simulation results show that the proposed algorithm gives higher face recognition accuracy, in comparison to the conventional methods.
|Original language||English (US)|
|Title of host publication||2016 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2016|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|State||Published - Nov 2 2016|