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Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments

Research article (2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023) · cited 15× · AI/ML
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Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments

Summary

Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments is a scholarly article[1].

Key Facts

  • Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments'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). Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments. Retrieved May 24, 2026, from https://4ort.xyz/entity/rawgment-noise-accounted-raw-augmentation-enables-recognition-in-a-wide-variety-of-environments
MLA “Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/rawgment-noise-accounted-raw-augmentation-enables-recognition-in-a-wide-variety-of-environments.
BibTeX @misc{4ortxyz_rawgment-noise-accounted-raw-augmentation-enables-recognition-in-a-wide-variety-of-environments_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments}}, year = {2026}, url = {https://4ort.xyz/entity/rawgment-noise-accounted-raw-augmentation-enables-recognition-in-a-wide-variety-of-environments}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments — https://4ort.xyz/entity/rawgment-noise-accounted-raw-augmentation-enables-recognition-in-a-wide-variety-of-environments (retrieved 2026-05-24)

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