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EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation

Research article (Neural Processing Letters, 2022) · cited 17× · AI/ML
academia openalex:W4207065174
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EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation

Summary

EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation is a scholarly article[1].

Key Facts

  • EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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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.

APA 4ort.xyz Knowledge Graph. (2026). EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation. Retrieved May 24, 2026, from https://4ort.xyz/entity/efrnet-efficient-feature-reuse-network-for-real-time-semantic-segmentation
MLA “EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/efrnet-efficient-feature-reuse-network-for-real-time-semantic-segmentation.
BibTeX @misc{4ortxyz_efrnet-efficient-feature-reuse-network-for-real-time-semantic-segmentation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation}}, year = {2026}, url = {https://4ort.xyz/entity/efrnet-efficient-feature-reuse-network-for-real-time-semantic-segmentation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): EFRNet: Efficient Feature Reuse Network for Real-time Semantic Segmentation — https://4ort.xyz/entity/efrnet-efficient-feature-reuse-network-for-real-time-semantic-segmentation (retrieved 2026-05-24)

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