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Quantum-Inspired Vision: Leveraging Wave-Particle Duality for Low-Illumination Enhancement

arXiv:2607.01731v1 Announce Type: cross Abstract: This study provides a theoretical expansion of the recent Data Relativistic Uncertainty (DRU) framework by formalizing a physics-to-AI paradigm for im

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arXiv:2607.01731v1 Announce Type: cross Abstract: This study provides a theoretical expansion of the recent Data Relativistic Uncertainty (DRU) framework by formalizing a physics-to-AI paradigm for image enhancement. By modeling images as probabilistic wave functions rather than deterministic states, the paradigm explicitly integrates wave-particle duality to illustrate the system flow of how DRU leverages the intrinsic physical uncertainty of light, a dimension requiring further theoretical discussion. Consequently, this paradigm provides a rigorous Explainable AI (XAI) approach that enhances the interpretability of how DRU mitigates illumination bias and maintains robustness against data noise.

Source: arXiv cs.LG | 2026-07-03

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