机器学习在核径迹探测器(NTD)图像分析中的顺序反卷积和卷积技术的应用
Application of Machine Learning on sequential deconvolution and convolution techniques for analysis of Nuclear Track Detector (NTD) images
摘要:
提出了一种新的核径迹探测器(NTD)图像分析算法。这个过程中,涉及顺序应用的反卷积和卷积技术,其次是人工神经网络(ANN)的应用程序,是识别NTD图像中的蚀坑开口与其他传统的图像分析技术相比,具有更高的成功程度。
英文摘要:
A novel image analysis algorithm as applied to images of Nuclear Track Detectors (NTD) is presented. This process, involving sequential application of deconvolution and convolution techniques, followed by the application of Artificial Neural Network (ANN), is identifying the etch-pit openings in NTD images with a higher degree of success compared to other conventional image analysis techniques.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。