Matches in SemOpenAlex for { <https://semopenalex.org/work/W2564975336> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W2564975336 abstract "Independent component analysis (ICA) is a multivariable statistical analysis method which can be applied for face recognition problem. The aim of recognition is to approximately estimate the components from the raw image. Components plays an important role in face recognition systems. Consequently, these components are used for extraction of face image features. However, these features may not be appropriate for classification, since the ICA method does not consider the class information. For the purpose of optimizing the performance of ICA, the discriminant ICA (dICA) method, which is a combination of ICA and LDA methods, is utilized for face recognition in this study. We have also proposed particle swarm optimization method to improve the dICA performance, in which PSO is used instead of the gradient approach for learning dICA. The results of PSO-dICA method confirm our idea in classification experiments compared to other methods. Using proposed method on Yale B dataset, gives an average classification accuracy of 92.169% compared with an accuracy of 91.322% using when dICA and accuracy of 89.77% compared with ICA and accuracy of 86.18% using PCA and also accuracy of 84.76% using LDA." @default.
- W2564975336 created "2017-01-06" @default.
- W2564975336 creator A5013841570 @default.
- W2564975336 creator A5032806407 @default.
- W2564975336 date "2016-10-01" @default.
- W2564975336 modified "2023-09-26" @default.
- W2564975336 title "Face recognition based on modified discriminant independent component analysis" @default.
- W2564975336 cites W1979245925 @default.
- W2564975336 cites W1982383215 @default.
- W2564975336 cites W1988914719 @default.
- W2564975336 cites W1990089311 @default.
- W2564975336 cites W1992688086 @default.
- W2564975336 cites W1995385879 @default.
- W2564975336 cites W1997903542 @default.
- W2564975336 cites W1998769964 @default.
- W2564975336 cites W2030837595 @default.
- W2564975336 cites W2075527894 @default.
- W2564975336 cites W2116019577 @default.
- W2564975336 cites W2123649031 @default.
- W2564975336 cites W2125213524 @default.
- W2564975336 cites W2133185047 @default.
- W2564975336 cites W2135463994 @default.
- W2564975336 cites W2139212933 @default.
- W2564975336 cites W2139896607 @default.
- W2564975336 cites W2146474141 @default.
- W2564975336 cites W2152195021 @default.
- W2564975336 cites W2181532327 @default.
- W2564975336 doi "https://doi.org/10.1109/iccke.2016.7802116" @default.
- W2564975336 hasPublicationYear "2016" @default.
- W2564975336 type Work @default.
- W2564975336 sameAs 2564975336 @default.
- W2564975336 citedByCount "3" @default.
- W2564975336 countsByYear W25649753362017 @default.
- W2564975336 countsByYear W25649753362018 @default.
- W2564975336 countsByYear W25649753362022 @default.
- W2564975336 crossrefType "proceedings-article" @default.
- W2564975336 hasAuthorship W2564975336A5013841570 @default.
- W2564975336 hasAuthorship W2564975336A5032806407 @default.
- W2564975336 hasConcept C119857082 @default.
- W2564975336 hasConcept C144024400 @default.
- W2564975336 hasConcept C153180895 @default.
- W2564975336 hasConcept C154945302 @default.
- W2564975336 hasConcept C27438332 @default.
- W2564975336 hasConcept C2779304628 @default.
- W2564975336 hasConcept C31510193 @default.
- W2564975336 hasConcept C36289849 @default.
- W2564975336 hasConcept C41008148 @default.
- W2564975336 hasConcept C51432778 @default.
- W2564975336 hasConcept C52622490 @default.
- W2564975336 hasConcept C69738355 @default.
- W2564975336 hasConcept C78397625 @default.
- W2564975336 hasConcept C85617194 @default.
- W2564975336 hasConceptScore W2564975336C119857082 @default.
- W2564975336 hasConceptScore W2564975336C144024400 @default.
- W2564975336 hasConceptScore W2564975336C153180895 @default.
- W2564975336 hasConceptScore W2564975336C154945302 @default.
- W2564975336 hasConceptScore W2564975336C27438332 @default.
- W2564975336 hasConceptScore W2564975336C2779304628 @default.
- W2564975336 hasConceptScore W2564975336C31510193 @default.
- W2564975336 hasConceptScore W2564975336C36289849 @default.
- W2564975336 hasConceptScore W2564975336C41008148 @default.
- W2564975336 hasConceptScore W2564975336C51432778 @default.
- W2564975336 hasConceptScore W2564975336C52622490 @default.
- W2564975336 hasConceptScore W2564975336C69738355 @default.
- W2564975336 hasConceptScore W2564975336C78397625 @default.
- W2564975336 hasConceptScore W2564975336C85617194 @default.
- W2564975336 hasLocation W25649753361 @default.
- W2564975336 hasOpenAccess W2564975336 @default.
- W2564975336 hasPrimaryLocation W25649753361 @default.
- W2564975336 hasRelatedWork W2067834828 @default.
- W2564975336 hasRelatedWork W2070644722 @default.
- W2564975336 hasRelatedWork W2104973399 @default.
- W2564975336 hasRelatedWork W2131248068 @default.
- W2564975336 hasRelatedWork W2141193014 @default.
- W2564975336 hasRelatedWork W2148040259 @default.
- W2564975336 hasRelatedWork W2148952803 @default.
- W2564975336 hasRelatedWork W2157903613 @default.
- W2564975336 hasRelatedWork W2160523419 @default.
- W2564975336 hasRelatedWork W2165555277 @default.
- W2564975336 hasRelatedWork W2347809599 @default.
- W2564975336 hasRelatedWork W2348059621 @default.
- W2564975336 hasRelatedWork W2348621841 @default.
- W2564975336 hasRelatedWork W2365455673 @default.
- W2564975336 hasRelatedWork W2374160781 @default.
- W2564975336 hasRelatedWork W2375412267 @default.
- W2564975336 hasRelatedWork W2381620968 @default.
- W2564975336 hasRelatedWork W2381775163 @default.
- W2564975336 hasRelatedWork W2384185843 @default.
- W2564975336 hasRelatedWork W2601157893 @default.
- W2564975336 isParatext "false" @default.
- W2564975336 isRetracted "false" @default.
- W2564975336 magId "2564975336" @default.
- W2564975336 workType "article" @default.