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dc.contributor.authorQahwaji, Rami S.R.*
dc.contributor.authorColak, Tufan*
dc.date.accessioned2016-01-27T09:50:37Z
dc.date.available2016-01-27T09:50:37Z
dc.date.issued2006
dc.identifier.citationQahwaji RSR and Colak T (2006) Hybrid imaging and neural networks techniques for processing solar images. International Journal of Computers and Applications. 13(9): 9-16.en_US
dc.identifier.urihttp://hdl.handle.net/10454/7720
dc.descriptionYesen_US
dc.description.abstractSolar imaging is currently an active area of research. A fast hybrid system for the automated detection of filaments in solar images is presented in this paper. The system includes three major stages. The central solar region is detected in the first stage using integral projections. Intensity filtering and image enhancement techniques are implemented in the second stage to enhance the quality of detection in the central region. Local detection windows are implemented in the third stage to detect the positions of filaments and to define various sized arrays to contain them. The extracted arrays are fed later to a neural network for verification purposes.en_US
dc.language.isoenen_US
dc.subjectSolar imaging; Space weather; Filaments detection; Segmentation; Neural networksen_US
dc.titleHybrid imaging and neural networks techniques for processing solar imagesen_US
dc.status.refereedYesen_US
dc.typeArticleen_US
dc.type.versionAccepted Manuscripten_US
refterms.dateFOA2018-07-25T12:34:25Z


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