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This is a Quantitative Study study.

September 20, 2025Journal of ImagingOpen Access

YOLO-DCRCF: An Algorithm for Detecting the Wearing of Safety Helmets and Gloves in Power Grid Operation Environments

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Novel YOLO-DCRCF algorithm improves detection accuracy of safety helmets and gloves, indicating better safety monitoring in power grid operations.

The YOLO-DCRCF model achieved mAP50 scores of 92.7% for safety helmets, showing significant detection capability.
On the Safety Helmet and Gloves Wearing Dataset, the model surpassed the baseline by 2.7%, indicating improved performance.
Utilizing Deformable Convolutional Network enhances the model’s ability to adapt to different geometric transformations effectively.
The recalibration feature pyramid network captures multi-scale information, which is critical for accurate detection in operations.

Zhao et al. (2025) studied this question.

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Novel YOLO-DCRCF algorithm improves detection accuracy of safety helmets and gloves, indicating better safety monitoring in power grid operations.