DocumentCode
1798334
Title
Incremental face recognition using rehearsal and recall processes
Author
Sangwook Kim ; Mallipeddi, R. ; Minho Lee
Author_Institution
Sch. of Electron. Eng., Kyungpook Nat. Univ., Taegu, South Korea
fYear
2014
fDate
6-11 July 2014
Firstpage
2752
Lastpage
2757
Abstract
Most of the machine learning algorithms particularly suffer from the plasticity-stability dilemma. In this paper, we propose a model that adopts two types of memories i.e. short-term memory (STM) and long-term memory (LTM), which share their information through control processes called rehearsal and recall to alleviate the dilemma. In addition, the proposed model tries to integrate the advantages of generative and discriminative classifiers by employing them in STM and LTM respectively. Experimental results show the importance of rehearsal and recall process in improving the performance of the algorithm.
Keywords
face recognition; image classification; learning (artificial intelligence); LTM learning process; STM learning process; discriminative classifiers; generative classifiers; incremental face recognition; long-term memory; recall process; rehearsal process; short-term memory; Data models; Face recognition; Feature extraction; Principal component analysis; Robustness; Support vector machines; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6627-1
Type
conf
DOI
10.1109/IJCNN.2014.6889902
Filename
6889902
Link To Document