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    A Global Feature Reused Network for Defect Detection in Steel Images 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 011:;page 114501-1
    Author(s): Yang, Chengli; Wang, Qingqing; Liu, Zhanqiang; Cheng, Yanhai
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Accurate detection of surface defects for steel is essential to improve surface quality and service life. Deep learning (DL) used in steel surface defect detection can solve the problems of low efficiency and poor accuracy ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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