Progressive degradation-aware distillation for robust indoor object detection
Researchers have developed 'Progressive Degradation-aware Distillation' (PDAD), a new training framework designed to improve indoor object detection in low-quality images. The method helps AI models maintain accuracy despite motion blur or sensor noise.
Why it matters
Advancements in robust object detection are critical for the development of reliable AR/VR interior design tools and automated home management systems.
Scientific Reports ( 2026 ) Cite this article
We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.
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