Home ›
Entities
› academia
› Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images
Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images
Research article (IEEE Geoscience and Remote Sensing Letters, 2022) · cited 20× · AI/ML
Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images
Summary
Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images is a scholarly article[1].
Key Facts
Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images'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). Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images. Retrieved May 24, 2026, from https://4ort.xyz/entity/hybridizing-euclidean-and-hyperbolic-similarities-for-attentively-refining-representations-in-semantic-segmentation-of-r
MLA“Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hybridizing-euclidean-and-hyperbolic-similarities-for-attentively-refining-representations-in-semantic-segmentation-of-r.
BibTeX@misc{4ortxyz_hybridizing-euclidean-and-hyperbolic-similarities-for-attentively-refining-representations-in-semantic-segmentation-of-r_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images}}, year = {2026}, url = {https://4ort.xyz/entity/hybridizing-euclidean-and-hyperbolic-similarities-for-attentively-refining-representations-in-semantic-segmentation-of-r}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Hybridizing Euclidean and Hyperbolic Similarities for Attentively Refining Representations in Semantic Segmentation of Remote Sensing Images — https://4ort.xyz/entity/hybridizing-euclidean-and-hyperbolic-similarities-for-attentively-refining-representations-in-semantic-segmentation-of-r (retrieved 2026-05-24)
