FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2312996138> ?p ?o ?g. }

• W2312996138 endingPage "4418" @default.
• W2312996138 startingPage "4402" @default.
• W2312996138 abstract "Hyperspectral remote sensing images, which are characterized by their high dimensionality, provide us with the capability to accurately identify objects on the ground. They can also be used to identify subclasses of objects. However, these subclasses are usually embedded in different subspaces due to the complex distribution of pixels in the feature space. In the literature, few hyperspectral image classification methods can take both the subclass and subspace into consideration at the same time. Motivated by the fact that natural DNA can distinguish biological subspecies (subclasses in hyperspectral images) using critical DNA fragments (subspaces in hyperspectral images), a semisupervised subspace-based DNA encoding and matching classifier for hyperspectral remote sensing imagery (SSDNA) is proposed in this paper. First, in the process of DNA encoding, the hyperspectral remote sensing image is transformed into a DNA cube, in which the first-order spectral curve of the hyperspectral remote sensing image is utilized in order to take the gradient information of the spectral curve into consideration. Second, in the process of DNA optimization, evolutionary algorithms are used to obtain the best DNA library of the typical objects, which includes the following: 1) A multicenter individual representation is designed in order to consider the existence of subclasses in the hyperspectral remote sensing image; 2) the unlabeled samples are utilized in the process of population initialization and fitness calculation to enhance the diversity of the population and the generalization of the classification performance; and 3) the different classes are embedded in different subspaces. A semisupervised technique is used to extract the subspaces, including the global subspace for all the classes and the local subspace for each class. Three hyperspectral data sets were tested and confirm that SSDNA performs better than the other supervised or semisupervised classifiers." @default.
• W2312996138 created "2016-06-24" @default.
• W2312996138 creator A5004831778 @default.
• W2312996138 creator A5026145013 @default.
• W2312996138 creator A5030713988 @default.
• W2312996138 creator A5066135984 @default.
• W2312996138 creator A5075903928 @default.
• W2312996138 date "2016-08-01" @default.
• W2312996138 modified "2023-09-26" @default.
• W2312996138 title "Semisupervised Subspace-Based DNA Encoding and Matching Classifier for Hyperspectral Remote Sensing Imagery" @default.
• W2312996138 cites W1522440472 @default.
• W2312996138 cites W1526295910 @default.
• W2312996138 cites W1646333690 @default.
• W2312996138 cites W1965038887 @default.
• W2312996138 cites W1972050808 @default.
• W2312996138 cites W1977312644 @default.
• W2312996138 cites W1980525840 @default.
• W2312996138 cites W1991003630 @default.
• W2312996138 cites W1991576946 @default.
• W2312996138 cites W1992314546 @default.
• W2312996138 cites W1997718749 @default.
• W2312996138 cites W2003182005 @default.
• W2312996138 cites W2003300916 @default.
• W2312996138 cites W2007496476 @default.
• W2312996138 cites W2008847349 @default.
• W2312996138 cites W2015511307 @default.
• W2312996138 cites W2026223678 @default.
• W2312996138 cites W2036298470 @default.
• W2312996138 cites W2041478093 @default.
• W2312996138 cites W2042564283 @default.
• W2312996138 cites W2056067618 @default.
• W2312996138 cites W2065991620 @default.
• W2312996138 cites W2066165847 @default.
• W2312996138 cites W2070424424 @default.
• W2312996138 cites W2073802252 @default.
• W2312996138 cites W2077196276 @default.
• W2312996138 cites W2087263574 @default.
• W2312996138 cites W2089731186 @default.
• W2312996138 cites W2096307073 @default.
• W2312996138 cites W2097915756 @default.
• W2312996138 cites W2114154403 @default.
• W2312996138 cites W2119363183 @default.
• W2312996138 cites W2127271355 @default.
• W2312996138 cites W2128550928 @default.
• W2312996138 cites W2134807165 @default.
• W2312996138 cites W2135758523 @default.
• W2312996138 cites W2136251662 @default.
• W2312996138 cites W2138973222 @default.
• W2312996138 cites W2142012908 @default.
• W2312996138 cites W2149939703 @default.
• W2312996138 cites W2149970733 @default.
• W2312996138 cites W2152057649 @default.
• W2312996138 cites W2153409933 @default.
• W2312996138 cites W2153635508 @default.
• W2312996138 cites W2159876240 @default.
• W2312996138 cites W2169042894 @default.
• W2312996138 cites W2280602655 @default.
• W2312996138 cites W2315461310 @default.
• W2312996138 cites W2328745260 @default.
• W2312996138 cites W2477202857 @default.
• W2312996138 cites W3150214740 @default.
• W2312996138 cites W2137033247 @default.
• W2312996138 doi "https://doi.org/10.1109/tgrs.2016.2541022" @default.
• W2312996138 hasPublicationYear "2016" @default.
• W2312996138 type Work @default.
• W2312996138 sameAs 2312996138 @default.
• W2312996138 citedByCount "20" @default.
• W2312996138 countsByYear W23129961382017 @default.
• W2312996138 countsByYear W23129961382018 @default.
• W2312996138 countsByYear W23129961382019 @default.
• W2312996138 countsByYear W23129961382020 @default.
• W2312996138 countsByYear W23129961382021 @default.
• W2312996138 countsByYear W23129961382022 @default.
• W2312996138 countsByYear W23129961382023 @default.
• W2312996138 crossrefType "journal-article" @default.
• W2312996138 hasAuthorship W2312996138A5004831778 @default.
• W2312996138 hasAuthorship W2312996138A5026145013 @default.
• W2312996138 hasAuthorship W2312996138A5030713988 @default.
• W2312996138 hasAuthorship W2312996138A5066135984 @default.
• W2312996138 hasAuthorship W2312996138A5075903928 @default.
• W2312996138 hasConcept C12362212 @default.
• W2312996138 hasConcept C144024400 @default.
• W2312996138 hasConcept C149923435 @default.
• W2312996138 hasConcept C153180895 @default.
• W2312996138 hasConcept C154945302 @default.
• W2312996138 hasConcept C159078339 @default.
• W2312996138 hasConcept C160633673 @default.
• W2312996138 hasConcept C205649164 @default.
• W2312996138 hasConcept C2524010 @default.
• W2312996138 hasConcept C2908647359 @default.
• W2312996138 hasConcept C31972630 @default.
• W2312996138 hasConcept C32834561 @default.
• W2312996138 hasConcept C33923547 @default.
• W2312996138 hasConcept C41008148 @default.
• W2312996138 hasConcept C62649853 @default.
• W2312996138 hasConcept C95623464 @default.
• W2312996138 hasConceptScore W2312996138C12362212 @default.
• W2312996138 hasConceptScore W2312996138C144024400 @default.

• next