Scipediacontent: Scipediacontent moved page Draft Content 110505213 to Rowlinson et al 2019a

2021-02-16T09:18:37Z

Scipediacontent moved page Draft Content 110505213 to Rowlinson et al 2019a

Scipediacontent: Created page with " == Abstract == With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it i..."

2021-02-16T09:18:33Z

Created page with " == Abstract == With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it i..."

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== Abstract ==

With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it impossible to manually analyse the datasets. Automated pipelines to process the information stored in the images are being developed, such as the LOFAR Transients Pipeline, outputting light curves and various transient parameters. These pipelines have a number of tuneable parameters that require training to meet the survey requirements. This paper utilises both observed and simulated datasets to demonstrate different machine learning strategies that can be used to train these parameters. The datasets used are from LOFAR observations and we process the data using the LOFAR Transients Pipeline; however the strategies developed are applicable to any light curve datasets at different frequencies and can be adapted to different automated pipelines. These machine learning strategies are publicly available as Python tools that can be downloaded and adapted to different datasets (https://github.com/AntoniaR/TraP_ML_tools).

Comment: Astronomy & Computing Accepted, 25 pages, 20 figure

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1808.07781 http://arxiv.org/abs/1808.07781]

* [https://dare.uva.nl/personal/pure/en/publications/identifying-transient-and-variable-sources-in-radio-images(dc4650d3-3e58-458f-97fb-c8e60909760d).html https://dare.uva.nl/personal/pure/en/publications/identifying-transient-and-variable-sources-in-radio-images(dc4650d3-3e58-458f-97fb-c8e60909760d).html]

* [https://hal-insu.archives-ouvertes.fr/insu-02123783 https://hal-insu.archives-ouvertes.fr/insu-02123783]

* [https://hal-insu.archives-ouvertes.fr/insu-02123783/file/28648.pdf https://hal-insu.archives-ouvertes.fr/insu-02123783/file/28648.pdf]

* [https://ir.cwi.nl/pub/28648 https://ir.cwi.nl/pub/28648]

* [http://dx.doi.org/10.1016/j.ascom.2019.03.003 http://dx.doi.org/10.1016/j.ascom.2019.03.003],
: [http://www.scopus.com/inward/record.url?scp=85064840104&partnerID=8YFLogxK http://www.scopus.com/inward/record.url?scp=85064840104&partnerID=8YFLogxK]

* [http://dx.doi.org/10.1016/j.ascom.2019.03.003 http://dx.doi.org/10.1016/j.ascom.2019.03.003],
: [https://ir.cwi.nl/pub/28648 https://ir.cwi.nl/pub/28648]

* [https://api.elsevier.com/content/article/PII:S2213133718301161?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S2213133718301161?httpAccept=text/xml],
: [https://api.elsevier.com/content/article/PII:S2213133718301161?httpAccept=text/plain https://api.elsevier.com/content/article/PII:S2213133718301161?httpAccept=text/plain],
: [http://dx.doi.org/10.1016/j.ascom.2019.03.003 http://dx.doi.org/10.1016/j.ascom.2019.03.003] under the license https://www.elsevier.com/tdm/userlicense/1.0/

* [https://hal-insu.archives-ouvertes.fr/insu-02123783 https://hal-insu.archives-ouvertes.fr/insu-02123783],
: [https://hal-insu.archives-ouvertes.fr/insu-02123783/document https://hal-insu.archives-ouvertes.fr/insu-02123783/document],
: [https://hal-insu.archives-ouvertes.fr/insu-02123783/file/28648.pdf https://hal-insu.archives-ouvertes.fr/insu-02123783/file/28648.pdf]

* [https://ui.adsabs.harvard.edu/abs/2019A%26C....27..111R/abstract https://ui.adsabs.harvard.edu/abs/2019A%26C....27..111R/abstract],
: [https://www.sciencedirect.com/science/article/pii/S2213133718301161 https://www.sciencedirect.com/science/article/pii/S2213133718301161],
: [https://pure.uva.nl/ws/files/46341747/Identifying_transient_and_variable_sources_in_radio_images_arXiv.pdf https://pure.uva.nl/ws/files/46341747/Identifying_transient_and_variable_sources_in_radio_images_arXiv.pdf],
: [https://www.narcis.nl/publication/RecordID/oai%3Acwi.nl%3A28648 https://www.narcis.nl/publication/RecordID/oai%3Acwi.nl%3A28648],
: [https://ir.cwi.nl/pub/28648 https://ir.cwi.nl/pub/28648],
: [https://ir.cwi.nl/pub/28648/28648.pdf https://ir.cwi.nl/pub/28648/28648.pdf],
: [https://academic.microsoft.com/#/detail/2888353656 https://academic.microsoft.com/#/detail/2888353656]

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Scipediacontent: Scipediacontent moved page Draft Content 110505213 to Rowlinson et al 2019a

Scipediacontent: Created page with " == Abstract == With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it i..."