3FGL J0928.3-5255 , the SIMBAD biblio

3FGL J0928.3-5255 , the SIMBAD biblio (21 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.16CEST10:04:05


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Title First 3 Authors
2013ApJS..209...34A viz 15       D               1 553 210 The first Fermi-LAT catalog of sources above 10 GeV. ACKERMANN M., AJELLO M., ALLAFORT A., et al.
2015ApJS..218...23A viz 16       D               1 3140 1411 Fermi Large Area Telescope third source catalog. ACERO F., ACKERMANN M., AJELLO M., et al.
2015A&A...581A..57L 16       D               2 42 6 Swift/XRT counterparts to unassociated Fermi high-energy LAT sources. LANDI R., BASSANI L., STEPHEN J.B., et al.
2016ApJ...820....8S viz 16       D               1 3047 91 Classification and ranking of Fermi LAT gamma-ray sources from the 3FGL catalog using machine learning techniques. SAZ PARKINSON P.M., XU H., YU P.L.H., et al.
2017A&A...602A..86L viz 16       D               2 1082 1 Research and characterisation of blazar candidates among the Fermi/LAT 3FGL catalogue using multivariate classifications. LEFAUCHEUR J. and PITA S.
2017MNRAS.470.1291S viz 16       D               1 563 2 3FGLzoo: classifying 3FGL unassociated Fermi-LAT γ-ray sources by artificial neural networks. SALVETTI D., CHIARO G., LA MURA G., et al.
2017ApJS..232...18A viz 16       D               1584 263 3FHL: the Third Catalog of Hard Fermi-LAT Sources. AJELLO M., ATWOOD W.B., BALDINI L., et al.
2019ApJ...871...94K 16       D               1 53 4 Identifying the 3FHL catalog. I. Archival Swift observations and source classification. KAUR A., AJELLO M., MARCHESI S., et al.
2019ApJ...887...18K viz 16       D               2 250 ~ Classification of new X-ray counterparts for Fermi unassociated gamma-ray sources using the Swift X-Ray Telescope. KAUR A., FALCONE A.D., STROH M.D., et al.
2019ApJ...887..104C 16       D               1 82 ~ Identifying TeV source candidates among Fermi-LAT unclassified blazars. CHIARO G., MEYER M., DI MAURO M., et al.
2020ApJS..247...33A viz 16       D               1 5175 880 Fermi Large Area Telescope fourth source catalog. ABDOLLAHI S., ACERO F., ACKERMANN M., et al.
2021ApJ...908..177K 17       D               1 109 ~ Classifying blazar candidates from the 3FGL unassociated catalog into BL Lacertae objects and flat spectrum radio quasars Using Swift and WISE data. KAUR A., FALCONE A.D. and STROH M.C.
2021AJ....161..154K viz 17       D               2 185 ~ X-ray spectra and multiwavelength machine learning classification for likely counterparts to Fermi 3FGL unassociated sources. KERBY S., KAUR A., FALCONE A.D., et al.
2021MNRAS.505.5853G 17       D               2 5834 ~ Artificial Neural Network classification of 4FGL sources. GERMANI S., TOSTI G., LUBRANO P., et al.
2021ApJ...923...75K viz 17       D               1 236 9 Multiwavelength spectral analysis and neural network classification of counterparts to 4FGL unassociated sources. KERBY S., KAUR A., FALCONE A.D., et al.
2022A&A...660A..87B viz 17       D               2 6191 10 Machine learning methods for constructing probabilistic Fermi-LAT catalogs. BHAT A. and MALYSHEV D.
2022ApJS..260...53A viz 17       D               1 6710 133 Incremental Fermi Large Area Telescope Fourth Source Catalog. ABDOLLAHI S., ACERO F., BALDINI L., et al.
2023ApJ...943..167K viz 17       D               2 116 4 Using Neural Networks to Differentiate Newly Discovered BL Lacertae Objects and FSRQs among the 4FGL Unassociated Sources Employing Gamma-Ray, X-Ray, UV/Optical, and IR Data. KAUR A., KERBY S. and FALCONE A.D.
2023MNRAS.523.5341T 17       D               1 104 ~ Classification of the Fermi-LAT blazar candidates of uncertain type using extreme gradient boosting. TOLAMATTI A., SINGH K.K. and YADAV K.K.
2023ApJ...951..133K viz 17       D               2 120 ~ Testing the Blazar Sequence with Spectra of Recently Discovered Dim Blazars from the Fermi Unassociated Catalog. KERBY S. and FALCONE A.D.
2026ApJ...999..244N 20       D               4 293 ~ Classification of a New X-Ray Catalog of Likely Counterparts to 4FGL-DR4 Unassociated Gamma-Ray Sources Using a Neural Network. NEUMANN K.D., FALCONE A.D., DIKERBY S., et al.

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