Article(id=1314908264484139382, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314908074188562588, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2026.04.029, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1773590400000, receivedDateStr=2026-03-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791428160066, onlineDateStr=2026-10-08, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791428160066, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791428160066, creator=13701087609, updateTime=1791428160066, updator=13701087609, issue=Issue{id=1314908074188562588, tenantId=1146029695717560320, journalId=1235980550691926019, year='2026', volume='46', issue='4', pageStart='1', pageEnd='266', issueExtLink='null', onlineDate='null', pubDate='1785513600000', pubDateStr='2026-08-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1791428114697, creator='13701087609', updateTime=1791430419337, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314917740654191268, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314908074188562588, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314917740654191269, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314908074188562588, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=190, endPage=195, ext={EN=ArticleExt(id=1314908264937124216, articleId=1314908264484139382, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=A Precursor Particle Detection Method Based on Improved Mask R-CNN, columnId=1236276106727321817, journalTitle=Mining and Metallurgical Engineering, columnName=METALLURGY, runingTitle=null, highlight=null, articleAbstract=

An improved Mask R-CNN based method for precursor particle detection is proposed. Multi-branch feature extraction is employed to capture particle features for feature fusion, and detection results of precursor particles are output through a dual-branch output module. The experimental results demonstrate that the proposed method achieves a detection accuracy of 93.2% for precursor particles, with an inference time of 15.1 ms per image. The model is characterized by both high accuracy and real-time inference efficiency, which can provide critical technical support for the production of highly-consistent precursor particles.

, authors=Zijian WU, Jingfeng XIAO, Xiaojun ZHUO, Yong HUANG, Xing XIA, authorsList=Zijian WU, Jingfeng XIAO, Xiaojun ZHUO, Yong HUANG, Xing XIA, authorCompany=null, correspAuthors=Xing XIA, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314908265637572986, articleId=1314908264484139382, tenantId=1146029695717560320, journalId=1235980550691926019, language=CN, title=基于改进Mask R-CNN的前驱体颗粒检测方法, columnId=1236276107322913000, journalTitle=矿冶工程杂志, columnName=冶金, runingTitle=null, highlight=null, articleAbstract=

提出基于改进Mask R-CNN的前驱体颗粒检测方法，通过多分支特征提取颗粒特征并进行特征融合，由双分支输出模块输出前驱体颗粒检测结果。结果表明，该方法可使前驱体颗粒检测准确率达93.2%，单张图像推理时间为15.1 ms。模型兼具较高精度与实时推理效率，可为高一致性前驱体颗粒生产提供关键技术支撑。

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武子健（2001—），男，安徽蚌埠人，硕士研究生，主要研究方向为计算机视觉与动力电池回收。E-mail: 2795446243@qq.com

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武子健（2001—），男，安徽蚌埠人，硕士研究生，主要研究方向为计算机视觉与动力电池回收。E-mail: 2795446243@qq.com

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