Guest editorial: new trends in data pre-processing methods for signal and image classification

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dc.authorid0000-0003-2689-8552en_US
dc.authorid0000-0002-8929-3473en_US
dc.authorid0000-0003-1840-9958en_US
dc.authorid0000-0003-1814-9682
dc.contributor.authorPolat, Kemal
dc.contributor.authorMuthusamy, Hariharan
dc.contributor.authorAcharya, Rajendra
dc.contributor.authorGuo, Yanhui
dc.date.accessioned2021-06-23T19:45:21Z
dc.date.available2021-06-23T19:45:21Z
dc.date.issued2017
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractA special issue of the Neural Computing and Applications (NCAA) is dedicated to ‘‘New trends in data pre-processing methods for signal and image classification.’’Data pre-processing is crucial for effective data mining. Low-quality data usually produce inaccurate and unpredictable outcomes. Today’s real-world data are greatly vulnerable to noise and getting lost due to either large data size or the sources of origin. Real-world data are often inconsistent and incomplete, and are possible to have several errors. These poor-quality data will result in poorquality mining outcomes. Data pre-processing enhances the data standard and subsequently aids to refine the value of data mining outcomes. Data pre-processing performs certain processing on raw original data to prepare it for further processing or analysis. In short, data pre-processing prepares original raw data for further processing. Data preprocessing converts the data into a form acceptable easily for further processing by the user.en_US
dc.identifier.doi10.1007/s00521-017-3202-6
dc.identifier.endpage2841en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-85029661606en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2839en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-017-3202-6
dc.identifier.urihttps://hdl.handle.net/20.500.12491/9140
dc.identifier.volume28en_US
dc.identifier.wosWOS:000426865100001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofNeural Computing & Applicationsen_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectData Pre-Processing Methodsen_US
dc.subjectSignal and Image Classification
dc.subjectNeural Computing
dc.titleGuest editorial: new trends in data pre-processing methods for signal and image classificationen_US
dc.typeEditorialen_US

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