Peer-reviewedCC BY 4.0Scientific Reports
A Gaussian quantum-inspired optimization framework for robust medical image watermarking
Related
- Quantum-inspired annealing-based semantic-aware optimization for sustainable cloud-edge intelligence
- The Overlap Gap Property: Separating Quantum and Quantum-Inspired Approximate Optimization Algorithms
- A hybrid bio-inspired optimization framework for modeling infant neurodevelopment from maternal mental health and biometric data
- A Dual-Stream Feature Learning Framework with Adaptive Bio-Inspired Protozoa-Starfish Optimization for Melanoma Classification.
- Landscape Limits of Quantum-Inspired Evolutionary Optimization across 256 continuous functions
BibTeX
@article{garg2026gaussian,
title = {{A Gaussian quantum-inspired optimization framework for robust medical image watermarking}},
author = {Preeti Garg and Madhu Gautam and Deepti Singh and Seema Maitrey and Addisalem Genta},
journal = {Scientific Reports},
year = {2026},
month = nov,
doi = {10.1038/s41598-026-73695-1},
url = {https://www.nature.com/articles/s41598-026-73695-1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A Gaussian quantum-inspired optimization framework for robust medical image watermarking
AU - Preeti Garg
AU - Madhu Gautam
AU - Deepti Singh
AU - Seema Maitrey
AU - Addisalem Genta
PY - 2026
DA - 2026/11/03
JO - Scientific Reports
DO - 10.1038/s41598-026-73695-1
UR - https://www.nature.com/articles/s41598-026-73695-1
SN - 2045-2322
ER -