Matches in SemOpenAlex for { <https://semopenalex.org/work/W2082419339> ?p ?o ?g. }
Showing items 1 to 61 of
61
with 100 items per page.
- W2082419339 endingPage "1789" @default.
- W2082419339 startingPage "1783" @default.
- W2082419339 abstract "This paper addresses the reliability of neuro-classifiers for paper currency recognition. A local principal component analysis (PCA) method is applied to remove non-linear dependencies among variables and extract the main principal features of data. At first the data space is partitioned into regions by using a self-organizing map (SOM) clustering and then the PCA is performed on each region. A learning vector quantization (LVQ) network is employed as the main classifier of the system. By defining a new algorithm for rating the reliability and using a set of test data, we estimate the reliability of the system. The experimental results taken from 1, 200 samples of US dollar bills show that the reliability is increased up to 100% when the number of regions as well as number of codebook vectors in the LVQ classifier are taken properly." @default.
- W2082419339 created "2016-06-24" @default.
- W2082419339 creator A5005208002 @default.
- W2082419339 creator A5031000559 @default.
- W2082419339 creator A5050766603 @default.
- W2082419339 date "2003-01-01" @default.
- W2082419339 modified "2023-09-23" @default.
- W2082419339 title "A Reliable Classification Method for Paper Currency Based on the Non-Linear PC" @default.
- W2082419339 cites W106987262 @default.
- W2082419339 cites W1680392829 @default.
- W2082419339 cites W2076175112 @default.
- W2082419339 cites W2115219969 @default.
- W2082419339 cites W2122538988 @default.
- W2082419339 cites W2126513157 @default.
- W2082419339 cites W2135346934 @default.
- W2082419339 cites W2233195300 @default.
- W2082419339 cites W2517574743 @default.
- W2082419339 doi "https://doi.org/10.1541/ieejeiss.123.1783" @default.
- W2082419339 hasPublicationYear "2003" @default.
- W2082419339 type Work @default.
- W2082419339 sameAs 2082419339 @default.
- W2082419339 citedByCount "1" @default.
- W2082419339 countsByYear W20824193392014 @default.
- W2082419339 crossrefType "journal-article" @default.
- W2082419339 hasAuthorship W2082419339A5005208002 @default.
- W2082419339 hasAuthorship W2082419339A5031000559 @default.
- W2082419339 hasAuthorship W2082419339A5050766603 @default.
- W2082419339 hasBestOaLocation W20824193391 @default.
- W2082419339 hasConcept C141121606 @default.
- W2082419339 hasConcept C153180895 @default.
- W2082419339 hasConcept C154945302 @default.
- W2082419339 hasConcept C162324750 @default.
- W2082419339 hasConcept C41008148 @default.
- W2082419339 hasConcept C556758197 @default.
- W2082419339 hasConceptScore W2082419339C141121606 @default.
- W2082419339 hasConceptScore W2082419339C153180895 @default.
- W2082419339 hasConceptScore W2082419339C154945302 @default.
- W2082419339 hasConceptScore W2082419339C162324750 @default.
- W2082419339 hasConceptScore W2082419339C41008148 @default.
- W2082419339 hasConceptScore W2082419339C556758197 @default.
- W2082419339 hasIssue "10" @default.
- W2082419339 hasLocation W20824193391 @default.
- W2082419339 hasOpenAccess W2082419339 @default.
- W2082419339 hasPrimaryLocation W20824193391 @default.
- W2082419339 hasRelatedWork W1532762289 @default.
- W2082419339 hasRelatedWork W1596801655 @default.
- W2082419339 hasRelatedWork W2358668433 @default.
- W2082419339 hasRelatedWork W2373011076 @default.
- W2082419339 hasRelatedWork W2376932109 @default.
- W2082419339 hasRelatedWork W2387147530 @default.
- W2082419339 hasRelatedWork W2390279801 @default.
- W2082419339 hasRelatedWork W2688602461 @default.
- W2082419339 hasRelatedWork W2748952813 @default.
- W2082419339 hasRelatedWork W2899084033 @default.
- W2082419339 hasVolume "123" @default.
- W2082419339 isParatext "false" @default.
- W2082419339 isRetracted "false" @default.
- W2082419339 magId "2082419339" @default.
- W2082419339 workType "article" @default.