黑龙江科技大学学报2024，Vol.34Issue(1)：157-162,6.DOI:10.3969/j.issn.2095-7262.2024.01.024
改进YOLOv7的煤岩图像检测算法
Coal rock image detection algorithm based on improved YOLOv7
摘要
Abstract
This paper proposes a coal rock image detection algorithm for improving YOLOv7 network structure by replacing some ordinary convolution modules,which is designed to address the problem that is hard to balance the accuracy and model scale in current coal rock image detection.The study is accom-plished by introducing ConvNeXt with a convolution kernel by 7 to replace the ordinary convolution mod-ule with the size 3×3 for improving the coal characteristics and obtaining the effect;using SimAM atten-tion mechanism to replace convolutional modules with the size 1×1 for creating MP_SAM modules to ena-ble the algorithm to extract more target information;optimizing the loss function by using αIoU to make it more suitable for coal rock images with insufficient clarity,and enhance the generalization ability of the algorithm.The experimental results show that,compared with YOLOv7 algorithm,the accuracy of the al-gorithm increases by 3.9%,the mAP increases by 1.5%,the overall FLOPs of the model are reduced by 0.7 G,and the detection results are better obtained by using the smaller model.关键词
煤岩检测/YOLOv7/SimAM/ConvNeXt/αIoUKey words
coal rock detection/YOLOv7/SimAM/ConvNeXt/αIoU分类
信息技术与安全科学引用本文复制引用
赵艳芹,邓虎诚..改进YOLOv7的煤岩图像检测算法[J].黑龙江科技大学学报,2024,34(1):157-162,6.基金项目
黑龙江省省属高等学校基本科研业务费项目(2022-KYYWF-0565) （2022-KYYWF-0565）
