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This research aims to enhance foreign object detection on conveyor belts using an improved YOLOv11 algorithm with ESRGAN.

May 15, 2026Scientific ReportsOpen Access

Conveyor belt foreign object detection method based on improved YOLOv11 and ESRGAN

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This research aims to enhance foreign object detection on conveyor belts using an improved YOLOv11 algorithm with ESRGAN.
Developed a custom dataset for conveyor belt environments
Integrated ESRGAN to enhance image resolution
Implemented architectural improvements in YOLOv11 for low-light conditions
YOLOv11-CBFD achieved 86.1% accuracy and 86.7% recall on the custom dataset
Reduced parameter count by 16.2%, maintaining performance
12.4% increase in frames per second on a Jetson Orin NX-embedded AI computer

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Randomized trial reveals enhanced detection accuracy in conveyor belt environments, indicating improved image recognition capabilities.

Li et al. (2026) studied this question.

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