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 |
|---|---|
| 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 |
|---|---|
| Country | Kazakhstan |
| City | Astana |
| Period | 8/15/18 → 8/17/18 |
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ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Electrical and Electronic Engineering
Cite this
An Improved Face Recognition Algorithm Based on Sparse Representation. / Turan, Cemil; Kadyrov, Shirali; Burissova, Diana.
Proceedings of the 2nd International Conference on Computing and Network Communications, CoCoNet 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 32-35 8476916.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An Improved Face Recognition Algorithm Based on Sparse Representation
AU - Turan, Cemil
AU - Kadyrov, Shirali
AU - Burissova, Diana
PY - 2018/9/28
Y1 - 2018/9/28
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85055986517&partnerID=8YFLogxK
U2 - 10.1109/CoCoNet.2018.8476916
DO - 10.1109/CoCoNet.2018.8476916
M3 - Conference contribution
SP - 32
EP - 35
BT - Proceedings of the 2nd International Conference on Computing and Network Communications, CoCoNet 2018
PB - Institute of Electrical and Electronics Engineers Inc.
ER -