Abstract
This paper considers a variation of Sparse Representation-based Classification algorithm. Accuracy and time of evaluation of face recognition are two key performance indicators. This work compares performance of modified Sparse Representation-based Classification algorithm against original Sparse Representation-based Classification algorithm. Yale Face Database B is used to carry MATLAB simulations and results show that modified Sparse Representation-based Classification algorithm outperforms in terms of time. Moreover, the authors study and compare these algorithms when there is only a few training samples per subject is available.
Original language | English |
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Title of host publication | Proceedings of the 2nd International Conference on Computing and Network Communications, CoCoNet 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 32-35 |
Number of pages | 4 |
ISBN (Electronic) | 9781538659281 |
DOIs | |
Publication status | Published - Sep 28 2018 |
Event | 2nd International Conference on Computing and Network Communications, CoCoNet 2018 - Astana, Kazakhstan Duration: Aug 15 2018 → Aug 17 2018 |
Conference
Conference | 2nd International Conference on Computing and Network Communications, CoCoNet 2018 |
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Country | Kazakhstan |
City | Astana |
Period | 8/15/18 → 8/17/18 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Electrical and Electronic Engineering