Related publications - Deyht/CIANNA GitHub Wiki
[Up to date with V-1.0.0.0 release]
List of talks from CIANNA lead developer that almost all reference the framework: list of conferences
Seminar at the LAB (Laboratoire d'Astrophysique de Bordeaux) presenting the framework itself: slides
List of (known) papers that make use of or directly refer to the CIANNA framework:
(For suggestions regarding this list, contact me directly at [email protected])
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Cornu et al. (in prep.) Galaxy detection with deep learning for radio-astronomical data. II. MINERVA: Winning the SKAO SDC2 using a 3D-YOLO-inspired source detection method. For submission to A&A, ...
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Kessler et al. (submitted) Identification of molecular line emission using Convolutional Neural Networks. Investigating molecular complexity Submitted to A&A, ...
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Cornu et al. (2024) Galaxy detection with deep learning for radio-astronomical data - I. A new YOLO-inspired source detection method applied to the SKAO SDC1, A&A, 690, A211, associated to CIANNA release 1.0.
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Kessler et al. (2023) SF2A-proceeding 2023, 2023sf2a.conf..303K, and paper in preparation.
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Hartley et al. (2023) SKA Science Data Challenge 2: analysis and results. MNRAS, Volume 523, Issue 2, 10.1093/mnras/stad1375
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Cornu et al. (2022) 3D extinction mapping of the Milky Way using Convolutional Neural Networks: Presentation of the method and demonstration in the Carina Arm region. arXiv:2201.05571
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Cornu et al. (2021) A neural network-based methodology to select young stellar object candidates from IR surveys. A&A, 647, A116
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Cornu et al. (2020) PhD Thesis: Modeling the 3D Milky Way using Machine Learning with Gaia and infrared surveys. arXiv:2010.01431