ISINA: INTEGRAL source identification network algorithm
TL;DR: In this paper, the authors present an overview of the ISINA: INTEGRAL Source Identification Network Algorithm, which is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues.
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Abstract: We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. First, we introduce the data set and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky. Three independent random forests are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples.
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Citations
Hard X-ray properties of magnetic cataclysmic variables*
Simone Scaringi,A. J. Bird,Andrew Norton,Christian Knigge,A. B. Hill,D. J. Clark,A. J. Dean,Vanessa McBride,E. J. Barlow,L. Bassani,Angela Bazzano,M. Fiocchi,R. Landi +12 more
TL;DR: In this article, the authors present a global study of hard X-ray-selected intermediate polars and asynchronous polars, focusing particularly on the link between hard Xray properties and spin/orbital periods.
Hard X-ray properties of magnetic cataclysmic variables
Simone Scaringi,A. J. Bird,Andrew Norton,Christian Knigge,A. B. Hill,D. J. Clark,A. J. Dean,Vanessa McBride,E. J. Barlow,L. Bassani,Angela Bazzano,M. Fiocchi,R. Landi +12 more
TL;DR: In this article, the authors present a global study of hard X-ray selected intermediate polars and asynchronous polars, focusing particularly on the link between hard Xray properties and spin/orbital periods.
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References
Random Forests
Leo Breiman
- 01 Oct 2001
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
SExtractor: Software for source extraction
E. Bertin,E. Bertin,S. Arnouts +2 more
TL;DR: The SExtractor ( Source Extractor) as mentioned in this paper is an automated software that optimally detects, deblends, measures and classifies sources from astronomical images, which is particularly suited to the analysis of large extragalactic surveys.