AF-FTTSnet: An end-to-end two-stream convolutional neural network for online quality monitoring of robotic welding

求助中 10 由 zqJAY 发布于 2024/10/5 20:03:31

DOI:10.1016/j.jmsy.2024.04.006
作者：Yuxiang Hong ,?Xingxing He ,?Jing Xu ,?Ruiling Yuan ,?Kai Lin ,?Baohua Chang ,?Dong Du
文献类型：期刊论文
补充材料：只需要正文

Elsevier

Abstract：Online welding quality monitoring (WQM) is crucial for intelligent welding, and deep learning approaches considering spatiotemporal features for WQM tasks show great potential. However, one

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上一个求助:其它数据库Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary 下一个求助:其它数据库END-TO-END PREDICTION OF WELD PENETRATION IN REAL TIME BASED ON DEEP LEARNING