An AI approach to lunar phase detection: enhancing the identification of the new crescent with astronomical data integration.

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Bibliographic Details
Title: An AI approach to lunar phase detection: enhancing the identification of the new crescent with astronomical data integration.
Authors: Al-Rajab M; College of Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates., Loucif S; College of Technological Innovation, Zayed University, Abu Dhabi, United Arab Emirates., Zitar RA; College of Engineering and Computing, Liwa University, Abu Dhabi, United Arab Emirates., Abdu-Aguye MG; Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates.
Source: Frontiers in artificial intelligence [Front Artif Intell] 2026 Feb 13; Vol. 9, pp. 1727824. Date of Electronic Publication: 2026 Feb 13 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101770551 Publication Model: eCollection Cited Medium: Internet ISSN: 2624-8212 (Electronic) Linking ISSN: 26248212 NLM ISO Abbreviation: Front Artif Intell Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2624-8212
DOI:10.3389/frai.2026.1727824