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FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution
Research article (2020 IEEE International Conference on Robotics and Automation (ICRA), 2020) · cited 26× · AI/ML
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution
Summary
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution is a scholarly article[1].
Key Facts
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution's instance of is recorded as scholarly article[2].
References
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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.
APA4ort.xyz Knowledge Graph. (2026). FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution. Retrieved May 24, 2026, from https://4ort.xyz/entity/farsee-net-real-time-semantic-segmentation-by-efficient-multi-scale-context-aggregation-and-feature-space-super-resoluti
MLA“FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/farsee-net-real-time-semantic-segmentation-by-efficient-multi-scale-context-aggregation-and-feature-space-super-resoluti.
BibTeX@misc{4ortxyz_farsee-net-real-time-semantic-segmentation-by-efficient-multi-scale-context-aggregation-and-feature-space-super-resoluti_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution}}, year = {2026}, url = {https://4ort.xyz/entity/farsee-net-real-time-semantic-segmentation-by-efficient-multi-scale-context-aggregation-and-feature-space-super-resoluti}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution — https://4ort.xyz/entity/farsee-net-real-time-semantic-segmentation-by-efficient-multi-scale-context-aggregation-and-feature-space-super-resoluti (retrieved 2026-05-24)
