Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding
Summary
Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding is a scholarly article[1].
Key Facts
Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding'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). Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding. Retrieved May 24, 2026, from https://4ort.xyz/entity/aircraft-detection-in-remote-sensing-images-based-on-a-deep-residual-network-and-super-vector-coding
MLA“Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/aircraft-detection-in-remote-sensing-images-based-on-a-deep-residual-network-and-super-vector-coding.
BibTeX@misc{4ortxyz_aircraft-detection-in-remote-sensing-images-based-on-a-deep-residual-network-and-super-vector-coding_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding}}, year = {2026}, url = {https://4ort.xyz/entity/aircraft-detection-in-remote-sensing-images-based-on-a-deep-residual-network-and-super-vector-coding}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Aircraft detection in remote sensing images based on a deep residual network and Super-Vector coding — https://4ort.xyz/entity/aircraft-detection-in-remote-sensing-images-based-on-a-deep-residual-network-and-super-vector-coding (retrieved 2026-05-24)
