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Texture image classification using pixel N-grams

Research article (2016 IEEE International Conference on Signal and Image Processing (ICSIP), 2016) · cited 28× · AI/ML
academia openalex:W2599945133
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Texture image classification using pixel N-grams

Summary

Texture image classification using pixel N-grams is a scholarly article[1].

Key Facts

  • Texture image classification using pixel N-grams'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). Texture image classification using pixel N-grams. Retrieved May 24, 2026, from https://4ort.xyz/entity/texture-image-classification-using-pixel-n-grams
MLA “Texture image classification using pixel N-grams.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/texture-image-classification-using-pixel-n-grams.
BibTeX @misc{4ortxyz_texture-image-classification-using-pixel-n-grams_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Texture image classification using pixel N-grams}}, year = {2026}, url = {https://4ort.xyz/entity/texture-image-classification-using-pixel-n-grams}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Texture image classification using pixel N-grams — https://4ort.xyz/entity/texture-image-classification-using-pixel-n-grams (retrieved 2026-05-24)

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