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Please use this identifier to cite or link to this item: http://hdl.handle.net/2289/8093
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dc.contributor.authorBhat, Shashank Sanjay-
dc.contributor.authorPrabu, Thiagaraj-
dc.contributor.authorStappers, Ben-
dc.contributor.authorGhalame, Atul-
dc.contributor.authorSaha, Snehanshu-
dc.contributor.authorSudarshan, T. S. B.-
dc.contributor.authorHosenie, Zafiirah-
dc.date.accessioned2023-05-01T08:32:55Z-
dc.date.available2023-05-01T08:32:55Z-
dc.date.issued2023-04-20-
dc.identifier.citationJournal of Astropysics and Astronomy, 2023, Vol. 44, Article No. - 36en_US
dc.identifier.issn0250-6335-
dc.identifier.issn0973-7758 (Online)-
dc.identifier.urihttp://hdl.handle.net/2289/8093-
dc.descriptionOpen Access from Indian Academy of Sciences, Bengaluruen_US
dc.description.abstractThe SKA pulsar search pipeline will be used for real time detection of pulsars. Modern radio telescopes, such as SKA will be generating petabytes of data in their full scale of operation. Hence, experience-based and data-driven algorithms are being investigated for applications, such as candidate detection. Here, we describe our findings from testing a state of the art object detection algorithm called Mask R-CNN to detect candidate signatures in the SKA pulsar search pipeline. We have trained the Mask R-CNN model to detect candidate images. A custom semi-auto annotation tool was developed and investigated to rapidly mark the regions of interest in large datasets. We have used a simulation dataset to train and build the candidate detection algorithm. A more detailed analysis is planned. This paper presents details of this initial investigation highlighting the future prospects.en_US
dc.language.isoenen_US
dc.publisherIndian Academy of Sciencesen_US
dc.relation.urihttps://arxiv.org/abs/2209.04430en_US
dc.relation.urihttps://ui.adsabs.harvard.edu/abs/2022arXiv220904430B/abstracten_US
dc.relation.urihttps://doi.org/10.1007/s12036-023-09920-4en_US
dc.rights2023 Indian Academy of Sceincesen_US
dc.titleInvestigation of a Machine learning methodology for the SKA pulsar search pipelineen_US
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