{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T15:26:08Z","timestamp":1740151568401,"version":"3.37.3"},"reference-count":13,"publisher":"Wiley","license":[{"start":{"date-parts":[[2012,8,30]],"date-time":"2012-08-30T00:00:00Z","timestamp":1346284800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"National Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]},{"name":"University of Calgary, Canada"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advances in Artificial Intelligence"],"published-print":{"date-parts":[[2012,8,30]]},"abstract":"<jats:p>Biometric pattern recognition emerged as one of the predominant research directions in modern security systems. It  plays a crucial role  in authentication of both  real-world  and virtual  reality  entities  to  allow  system  to  make  an  informed decision on granting  access privileges or providing specialized services. The major issues tackled  by the researchers are arising from the ever-growing demands  on precision and performance of security  systems and  at  the same  time  increasing  complexity  of data  and\/or behavioral patterns to be recognized. In this paper, we  propose  to  deal  with  both  issues  by  introducing  the  new approach  to  biometric   pattern  recognition,   based   on  chaotic neural network  (CNN). The  proposed  method  allows learning the complex data patterns easily while concentrating on the most important  for  correct  authentication  features  and  employs  a unique method to train different classifiers based on each feature set. The aggregation result depicts the final decision over the recognized identity.  In order to train accurate set of classifiers, the subspace clustering method has been used to overcome the problem of high dimensionality of the feature space. The experimental results show the superior performance of the proposed method.<\/jats:p>","DOI":"10.1155\/2012\/124176","type":"journal-article","created":{"date-parts":[[2012,8,30]],"date-time":"2012-08-30T21:01:33Z","timestamp":1346360493000},"page":"1-9","source":"Crossref","is-referenced-by-count":5,"title":["Chaotic Neural Network for Biometric Pattern Recognition"],"prefix":"10.1155","volume":"2012","author":[{"given":"Kushan","family":"Ahmadian","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Calgary, Calgary, AB, Canada T2N 1N4"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marina","family":"Gavrilova","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Calgary, Calgary, AB, Canada T2N 1N4"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"12","doi-asserted-by":"publisher","DOI":"10.1126\/science.290.5500.2323"},{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1008383"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/34.598235"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2002.804287"},{"issue":"7","key":"2","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/34.598228","volume":"19","year":"1997","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/97.991133"},{"issue":"10","key":"5","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.1162\/089976600300014980","volume":"12","year":"2000","journal-title":"Neural Computation"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/72.750575"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001410008391"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1504\/IJITM.2012.044061"},{"issue":"1","key":"18","first-page":"1","volume":"3","year":"2009","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"key":"15","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1080\/03081088508817681","volume":"18","year":"1985","journal-title":"Linear and Multilinear Algebra"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-005-4939-z"}],"container-title":["Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/archive\/2012\/124176.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/archive\/2012\/124176.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/archive\/2012\/124176.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T03:28:31Z","timestamp":1607570911000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/aai\/2012\/124176\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,8,30]]},"references-count":13,"alternative-id":["124176","124176"],"URL":"https:\/\/doi.org\/10.1155\/2012\/124176","relation":{},"ISSN":["1687-7470","1687-7489"],"issn-type":[{"type":"print","value":"1687-7470"},{"type":"electronic","value":"1687-7489"}],"subject":[],"published":{"date-parts":[[2012,8,30]]}}}