Journal ArticleDOI
A study of hybrid neural network to improve performance of face recognition
Sung-Boo Chung,Joo-Woong Kim +1 more
TLDR
A hybrid neural network is proposed for improve the performance of the face recognition by consisted of SOM and LVQ and a comparison is made between eigenface method, hidden Markov model method, multi-layer neural network.Abstract:
The accuracy of face recognition used unmanned security system is very important and necessary. However, face recognition is a lot of restriction due to the change of distortion of face image, illumination, face size, face expression, round image. We propose a hybrid neural network for improve the performance of the face recognition. The proposed method is consisted of SOM and LVQ. In order to verify usefulness of the proposed method, we make a comparison between eigenface method, hidden Markov model method, multi-layer neural network.read more
Citations
More filters
Journal ArticleDOI
Analysis on the Distribution of RF Threats Using Unsupervised Learning Techniques
TL;DR: A method to analyze the clusters of RF threats emitting electrical signals based on collected signal variables in integrated electronic warfare environments using k-means clustering algorithm and self-organizing map algorithm, which are belonging to unsupervised learning techniques.
References
More filters
Journal ArticleDOI
Human and machine recognition of faces: a survey
TL;DR: A critical survey of existing literature on human and machine recognition of faces is presented, followed by a brief overview of the literature on face recognition in the psychophysics community and a detailed overview of move than 20 years of research done in the engineering community.
ReportDOI
Support Vector Machines Applied to Face Recognition
TL;DR: A SVM -based face recognition algorithm that is compared with a principal component analysis (PCA) based algorithm on a difficult set of images from the FERET database and generated a similarity metric between faces that is learned from examples of differences between faces.
Book ChapterDOI
Face Recognition Using Independent Component Analysis and Support Vector Machines
TL;DR: This result indicates that the best practical combination is PCA with SVM as the training time for ICA is much larger than that of PCA, and SVMs are relatively insensitive to the representation space.
Proceedings ArticleDOI
A new method for initializing reference vectors in LVQ
TL;DR: A new method for setting initial locations of reference vectors in learning vector quantization (LVQ) is proposed to obtain stably high-performance classification results and numerical simulations confirm better classification results with the present method than with conventional methods.
Proceedings ArticleDOI
LVQ with a weighted objective function
Su-Jeong You,Chong-Ho Choi +1 more
TL;DR: It is shown from simulation results that the proposed algorithm gives better performance than other algorithms in clustering, a variety of GLVQ, and is compared with other algorithms.