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The study aims to develop an automated method for detecting Yuxian paper-cut opera figures to assist in their digital preservation.

July 24, 2026ElectronicsOpen Access

Visual-Type Detection of Yuxian Paper-Cut Opera Figures for Digital Preservation of Intangible Cultural Heritage: A YOLOv8-SCSA-Based Approach

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Randomized trial demonstrates enhanced object detection in Yuxian paper-cut figures, suggesting improved digital preservation techniques.

The study aims to develop an automated method for detecting Yuxian paper-cut opera figures to assist in their digital preservation.
Constructed a curated dataset of 926 images with 976 annotated instances across three visual categories.
Adapted a YOLOv8n-based detector integrating the Spatial and Channel Synergistic Attention (SCSA) module and Inner-IoU regression strategy.
Evaluated detection performance using precision, recall, and mAP metrics on a test set.
Achieved 95.8% precision, 92.9% recall, 98.8% mAP@0.5, and 89.6% mAP@0.5:0.95, exceeding baseline metrics.
Combined SCSA placement with Inner-IoU yielded the highest detection performance.
Forward-pass throughput reached 92.3 FPS under the GPU configuration used.

Huang et al. (2026) studied this question.

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