A Lightweight YOLOv7‐Based Algorithm for Detecting Foreign Objects on Coal Conveyors

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This algorithm enhances detection accuracy and speed in low-light conditions on coal conveyors, implying a safer mining process.

The improved YOLOv7 algorithm reduces detection time by 3.9 ms and increases accuracy by 1.1%.
Image enhancement techniques significantly improve feature information of foreign objects in low-light settings.
The algorithm uses a modified ShuffleNetv2 to achieve a lightweight design, maintaining detection performance effectively.
Including squeeze and excitation modules minimizes precision loss while simplifying the model for edge devices.

Zhang et al. (2025) studied this question.

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