Astronomical source finding services for the CIRASA visual analytic platform
원문 초록
Innovative developments in data processing, archiving, analysis, and visualization are nowadays unavoidable to deal with the data deluge expected in next-generation facilities for radio astronomy, such as the Square Kilometre Array (SKA) and its precursors. In this context, the integration of source extraction and analysis algorithms into data visualization tools could significantly improve and speed up the cataloguing process of large area surveys, boosting astronomer productivity and shortening publication time. To this aim, we are developing a visual analytic platform (CIRASA) for advanced source finding and classification, integrating state-of-the-art tools, such as the CAESAR source finder, the ViaLactea Visual Analytic (VLVA) and Knowledge Base (VLKB). In this work, we present the project objectives and the platform architecture, focusing on the implemented source finding services.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Statistical Machine Learning for Astronomy -- A Textbook
Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy Morphology Augmentation
Capturing Visualization Design Rationale
VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generation
Emulating compact binary population synthesis simulations with robust uncertainty quantification and model comparison: Bayesian normalizing flows
Mapping correlations and coherence: adjacency-based approach to data visualization and regularity discovery
토론
이 논문과 연결된 포럼 글이 아직 없습니다.