针对印刷电路板(Printed Circuit Board,PCB)表面缺陷检测任务中模型体积和参数量较大的问题,提出了一种基于通道剪枝的轻量级YOLOv8n网络PCB缺陷检测算法。为有效提升对PCB小目标缺陷的特征提取能力,采用RepViT作为特征提取网络;为提...针对印刷电路板(Printed Circuit Board,PCB)表面缺陷检测任务中模型体积和参数量较大的问题,提出了一种基于通道剪枝的轻量级YOLOv8n网络PCB缺陷检测算法。为有效提升对PCB小目标缺陷的特征提取能力,采用RepViT作为特征提取网络;为提升网络对小目标的关注度,减少神经网络推理过程中的梯度信息重复,将颈部网络的卷积模块替换为Rep-Net with Cross-Stage Partial CSP and ELAN(RepNCSPELAN4);为降低缺陷重叠时检测框失真现象,在预测部分使用Focaler-MPDIoU替换完全交并比(Complete Intersection over Union,CIoU);利用层自适应幅度分数剪枝(Layer Adaptive Magnitude based Pruning,LAMP)方法对融合改进方法的模型进行修剪,去除模型中冗余的梯度信息和权重,减少参数量和浮点运算量,压缩模型体积。实验结果表明,在PCB公开数据集中,经过LAMP之后,该算法相较于YOLOv8n,参数量下降60.8%,模型体积减小50.8%,计算量下降48.8%,平均精度均值(mean Average Precision,mAP)提高3.8%。在提高精度的同时,计算量、参数量和模型体积都低于原模型,满足在低配置设备下的使用需求。展开更多
With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to d...With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.展开更多
文摘针对印刷电路板(Printed Circuit Board,PCB)表面缺陷检测任务中模型体积和参数量较大的问题,提出了一种基于通道剪枝的轻量级YOLOv8n网络PCB缺陷检测算法。为有效提升对PCB小目标缺陷的特征提取能力,采用RepViT作为特征提取网络;为提升网络对小目标的关注度,减少神经网络推理过程中的梯度信息重复,将颈部网络的卷积模块替换为Rep-Net with Cross-Stage Partial CSP and ELAN(RepNCSPELAN4);为降低缺陷重叠时检测框失真现象,在预测部分使用Focaler-MPDIoU替换完全交并比(Complete Intersection over Union,CIoU);利用层自适应幅度分数剪枝(Layer Adaptive Magnitude based Pruning,LAMP)方法对融合改进方法的模型进行修剪,去除模型中冗余的梯度信息和权重,减少参数量和浮点运算量,压缩模型体积。实验结果表明,在PCB公开数据集中,经过LAMP之后,该算法相较于YOLOv8n,参数量下降60.8%,模型体积减小50.8%,计算量下降48.8%,平均精度均值(mean Average Precision,mAP)提高3.8%。在提高精度的同时,计算量、参数量和模型体积都低于原模型,满足在低配置设备下的使用需求。
基金Project supported by the National Natural Science Foundation of China(Grant No.T2293771)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.
