@article{MAKHILLAJIT20065115232,
    title = {Multi-Agent Based Facial Recognition System Using RETSINA},
    journal = {Asian Journal of Information Technology},
    volume = {5},
    number = {11},
    pages = {1177-1179},
    year = {2006},
    issn = {1682-3915},
    doi = {ajit.2006.1177.1179},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2006.1177.1179},
    author = {K.L. Shunmuganathan and},
    keywords = {Multi-agents,agent communication language,RETSINA,biometrics,principal component analysis,eigenvectors,feature extraction,covariance matrix},
    abstract = {We propose an appearance-based facial recognition system based on multi-agents. By this method a person can  be  identified and verified using his face. Each RETSINA agent performs the facial recognition with its own small training sets and its stops other agents when it finds a match by communicating through ACL. Experimental results suggest that the proposed multi-agent based Facial recognition method provides a better recognition rate and achieves less time complexity. The worst case analysis shows proposed multi-agent based facial recognition is 80% better than ordinary facial recognition.}
    }