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  • 标题:Iris Recognition Using Modified Fuzzy Hypersphere Neural Network with different Distance Measures
  • 本地全文:下载
  • 作者:S Chowhan ; U. V. Kulkarni ; G. N. Shinde
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2011
  • 卷号:2
  • 期号:6
  • DOI:10.14569/IJACSA.2011.020619
  • 出版社:Science and Information Society (SAI)
  • 摘要:In this paper we describe Iris recognition using Modified Fuzzy Hypersphere Neural Network (MFHSNN) with its learning algorithm, which is an extension of Fuzzy Hypersphere Neural Network (FHSNN) proposed by Kulkarni et al. We have evaluated performance of MFHSNN classifier using different distance measures. It is observed that Bhattacharyya distance is superior in terms of training and recall time as compared to Euclidean and Manhattan distance measures. The feasibility of the MFHSNN has been successfully appraised on CASIA database with 756 images and found superior in terms of generalization and training time with equivalent recall time.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Bhattacharyya distance; Iris Segmentation; Fuzzy Hypersphere Neural Network.
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