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An Efficient Adaptive Network-Based Fuzzy Inference System with Mosquito Host-Seeking For Facial Expression Recognition

M. Carmel Sobia1, A. Abudhahir2

1 Asst.Prof. (S.G), EIE, National Engineering College, Kovilpatti, Tamilnadu, India.
2 Prof. EEE, Vel Tech MultitechDr.RangarajanDr.Sakunthala Engineering College, Chennai.

* Corresponding Author: M. Carmel Sobia, email

Intelligent Automation & Soft Computing 2018, 24(4), 869-881.


In this paper, an efficient facial expression recognition system using ANFIS-MHS (Adaptive Network-based Fuzzy Inference System with Mosquito Host-Seeking) has been proposed. The features were extracted using MLDA (Modified Linear Discriminant Analysis) and then the optimized parameters are computed by using mGSO (modified Glow-worm Swarm Optimization).The proposed system recognizes the facial expressions using ANFIS-MHS. The experimental results demonstrate that the proposed technique is performed better than existing classification schemes like HAKELM (Hybridization of Adaptive Kernel based Extreme Learning Machine), Support Vector Machine (SVM) and Principal Component Analysis (PCA). The proposed approach is implemented in MATLAB.


Cite This Article

M. C. Sobia and A. Abudhahir, "An efficient adaptive network-based fuzzy inference system with mosquito host-seeking for facial expression recognition," Intelligent Automation & Soft Computing, vol. 24, no.4, pp. 869–881, 2018.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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