Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks

Research article (Multidimensional Systems and Signal Processing, 2017) · cited 32× · AI/ML
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Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks

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Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks. Retrieved May 24, 2026, from https://4ort.xyz/entity/utilizing-neighborhood-coefficient-correlation-a-new-image-watermarking-technique-robust-to-singular-and-hybrid-attacks
MLA “Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/utilizing-neighborhood-coefficient-correlation-a-new-image-watermarking-technique-robust-to-singular-and-hybrid-attacks.
BibTeX @misc{4ortxyz_utilizing-neighborhood-coefficient-correlation-a-new-image-watermarking-technique-robust-to-singular-and-hybrid-attacks_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks}}, year = {2026}, url = {https://4ort.xyz/entity/utilizing-neighborhood-coefficient-correlation-a-new-image-watermarking-technique-robust-to-singular-and-hybrid-attacks}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks — https://4ort.xyz/entity/utilizing-neighborhood-coefficient-correlation-a-new-image-watermarking-technique-robust-to-singular-and-hybrid-attacks (retrieved 2026-05-24)

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