Home ›
Entities
› academia
› Deep learning approach for identification of <scp>H ii</scp> regions during reionization in 21-cm observations – II. Foreground contamination
Deep learning approach for identification of <scp>H ii</scp> regions during reionization in 21-cm observations – II. Foreground contamination
Research article (Monthly Notices of the Royal Astronomical Society, 2024) · cited 21× · AI/ML
Deep learning approach for identification of H ii regions during reionization in 21-cm observations – II. Foreground contamination
Summary
Deep learning approach for identification of H ii regions during reionization in 21-cm observations – II. Foreground contamination is a scholarly article[1].
Key Facts
Deep learning approach for identification of H ii regions during reionization in 21-cm observations – II. Foreground contamination's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Deep learning approach for identification of <scp>H ii</scp> regions during reionization in 21-cm observations – II. Foreground contamination. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-approach-for-identification-of-scp-h-ii-scp-regions-during-reionization-in-21-cm-observations-ii-foregroun
MLA“Deep learning approach for identification of <scp>H ii</scp> regions during reionization in 21-cm observations – II. Foreground contamination.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-approach-for-identification-of-scp-h-ii-scp-regions-during-reionization-in-21-cm-observations-ii-foregroun.
BibTeX@misc{4ortxyz_deep-learning-approach-for-identification-of-scp-h-ii-scp-regions-during-reionization-in-21-cm-observations-ii-foregroun_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep learning approach for identification of <scp>H ii</scp> regions during reionization in 21-cm observations – II. Foreground contamination}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-approach-for-identification-of-scp-h-ii-scp-regions-during-reionization-in-21-cm-observations-ii-foregroun}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep learning approach for identification of <scp>H ii</scp> regions during reionization in 21-cm observations – II. Foreground contamination — https://4ort.xyz/entity/deep-learning-approach-for-identification-of-scp-h-ii-scp-regions-during-reionization-in-21-cm-observations-ii-foregroun (retrieved 2026-05-24)
