基于YOLOv5的煤矸石智能分选系统

2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML) Pub Date : 2022-03-01 DOI:10.1109/CACML55074.2022.00088

Pan Xin, Z. Dong

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引用次数: 0

摘要

针对传统煤炭行业矸石分选依赖人力、消耗资源多的问题，自制的矸石、煤训练集，结合目标检测的YOLO算法，实现了矸石、煤的识别与区分。实验表明，该方法快速、准确地区分了煤矸石，达到了预期效果。

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Intellegent Coal Gangue Sorting System Based on YOLOv5

Aiming at the problem of relying on manpower and consuming a lot of resources in the sorting of gangue in the traditional coal industry, the self-made training set of gangue and coal, combined with the YOLO algorithm of target detection, realized the identification and distinction of gangue and coal. Experiments show that the method is fast and can more accurately distinguish coal and gangue, and achieves the expected effect.

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2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)

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