FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3014158093> ?p ?o ?g. }

• W3014158093 endingPage "290" @default.
• W3014158093 startingPage "267" @default.
• W3014158093 abstract "Because of high dimensionality, correlation among covariates, and noise contained in data, dimension reduction (DR) techniques are often employed to the application of machine learning algorithms. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and their kernel variants (KPC A, KLDA) are among the most popular DR methods. Recently, Supervised Kernel Principal Component Analysis (SKPCA) has been shown as another successful alternative. In this paper, brief reviews of these popular techniques are presented first. We then conduct a comparative performance study based on three simulated datasets, after which the performance of the techniques are evaluated through application to a pattern recognition problem in face image analysis. The gender classification problem is considered on MORPH-II and FG-NET, two popular longitudinal face aging databases. Several feature extraction methods are used, including biologically-inspired features (BIF), local binary patterns (LBP), histogram of oriented gradients (HOG), and the Active Appearance Model (AAM). After applications of DR methods, a linear support vector machine (SVM) is deployed with gender classification accuracy rates exceeding 95% on MORPH-II, competitive with benchmark results. A parallel computational approach is also proposed, attaining faster processing speeds and similar recognition rates on MORPH-II. Our computational approach can be applied to practical gender classification systems and generalized to other face analysis tasks, such as race classification and age prediction." @default.
• W3014158093 created "2020-04-10" @default.
• W3014158093 creator A5014052149 @default.
• W3014158093 creator A5018688733 @default.
• W3014158093 creator A5026713161 @default.
• W3014158093 creator A5027329732 @default.
• W3014158093 date "2020-03-27" @default.
• W3014158093 modified "2023-10-06" @default.
• W3014158093 title "A comparison study on nonlinear dimension reduction methods with kernel variations: Visualization, optimization and classification" @default.
• W3014158093 cites W1514415280 @default.
• W3014158093 cites W1540155273 @default.
• W3014158093 cites W1587559447 @default.
• W3014158093 cites W1638081485 @default.
• W3014158093 cites W1761337995 @default.
• W3014158093 cites W1919814523 @default.
• W3014158093 cites W1941659294 @default.
• W3014158093 cites W1964749215 @default.
• W3014158093 cites W1971957654 @default.
• W3014158093 cites W1974097586 @default.
• W3014158093 cites W1977050089 @default.
• W3014158093 cites W1978675111 @default.
• W3014158093 cites W1984849553 @default.
• W3014158093 cites W2001003881 @default.
• W3014158093 cites W2011688148 @default.
• W3014158093 cites W2030818161 @default.
• W3014158093 cites W2033381780 @default.
• W3014158093 cites W2041657594 @default.
• W3014158093 cites W2044730627 @default.
• W3014158093 cites W2071128523 @default.
• W3014158093 cites W2090341258 @default.
• W3014158093 cites W2094248163 @default.
• W3014158093 cites W2094977433 @default.
• W3014158093 cites W2095193916 @default.
• W3014158093 cites W2096336206 @default.
• W3014158093 cites W2098072631 @default.
• W3014158093 cites W2098790407 @default.
• W3014158093 cites W2100495367 @default.
• W3014158093 cites W2102544846 @default.
• W3014158093 cites W2104320981 @default.
• W3014158093 cites W2105026179 @default.
• W3014158093 cites W2111146558 @default.
• W3014158093 cites W2115394472 @default.
• W3014158093 cites W2121647436 @default.
• W3014158093 cites W2121654450 @default.
• W3014158093 cites W2134262590 @default.
• W3014158093 cites W2137802466 @default.
• W3014158093 cites W2138451337 @default.
• W3014158093 cites W2140095548 @default.
• W3014158093 cites W2141381813 @default.
• W3014158093 cites W2143304877 @default.
• W3014158093 cites W2146656095 @default.
• W3014158093 cites W2149494055 @default.
• W3014158093 cites W2150796457 @default.
• W3014158093 cites W2172803778 @default.
• W3014158093 cites W2179234838 @default.
• W3014158093 cites W2274745179 @default.
• W3014158093 cites W2294798173 @default.
• W3014158093 cites W2295055508 @default.
• W3014158093 cites W2492307518 @default.
• W3014158093 cites W2588729078 @default.
• W3014158093 cites W2731793484 @default.
• W3014158093 cites W2750378047 @default.
• W3014158093 cites W2963112378 @default.
• W3014158093 cites W4298876635 @default.
• W3014158093 doi "https://doi.org/10.3233/ida-194486" @default.
• W3014158093 hasPublicationYear "2020" @default.
• W3014158093 type Work @default.
• W3014158093 sameAs 3014158093 @default.
• W3014158093 citedByCount "7" @default.
• W3014158093 countsByYear W30141580932021 @default.
• W3014158093 countsByYear W30141580932022 @default.
• W3014158093 crossrefType "journal-article" @default.
• W3014158093 hasAuthorship W3014158093A5014052149 @default.
• W3014158093 hasAuthorship W3014158093A5018688733 @default.
• W3014158093 hasAuthorship W3014158093A5026713161 @default.
• W3014158093 hasAuthorship W3014158093A5027329732 @default.
• W3014158093 hasBestOaLocation W30141580932 @default.
• W3014158093 hasConcept C114614502 @default.
• W3014158093 hasConcept C115961682 @default.
• W3014158093 hasConcept C119857082 @default.
• W3014158093 hasConcept C122280245 @default.
• W3014158093 hasConcept C12267149 @default.
• W3014158093 hasConcept C13280743 @default.
• W3014158093 hasConcept C153180895 @default.
• W3014158093 hasConcept C154945302 @default.
• W3014158093 hasConcept C181367576 @default.
• W3014158093 hasConcept C182335926 @default.
• W3014158093 hasConcept C185798385 @default.
• W3014158093 hasConcept C202444582 @default.
• W3014158093 hasConcept C205649164 @default.
• W3014158093 hasConcept C27438332 @default.
• W3014158093 hasConcept C31510193 @default.
• W3014158093 hasConcept C33676613 @default.
• W3014158093 hasConcept C33923547 @default.
• W3014158093 hasConcept C41008148 @default.
• W3014158093 hasConcept C52622490 @default.
• W3014158093 hasConcept C53533937 @default.
• W3014158093 hasConcept C69738355 @default.

• next