基于深度学习的液压支架支护质量评价方法研究

Research on Hydraulic Support Supporting Quality Evaluation Method Based on Deep Learning

为提高液压支架支护质量评价方法的操作效率和精度,提出一种基于深度学习模型的评价方法,将液压支架支护质量的评价问题转化为图像分类问题。结果表明,该评价方法在计算复杂度降低1/2的条件下取得了出色的分类精度(82.74%)和准确的定位精度(81.67%),具有明显的计算优势。

In order to improve the operational efficiency and accuracy of the evaluation method for the supporting quality of hydraulic support,proposed an evaluation method based on the deep learning model,which the evaluation problem of hydraulic support supporting quality is transformed into an image classification problem.The results show that this evaluation method can achieve a classification accuracy of 89.07%and a positioning accuracy of 81.67%,which has obvious calculation advantage.