A novel image analysis algorithm, applied to the images from Nuclear Track Detectors (NTDs), is presented. This process, involving the sequential application of deconvolution and convolution techniques, followed by the application of Artificial Neural Network (ANN), to identify the etch-pit openings in NTDs, gives a higher degree of success compared to other conventional image analysis techniques.

中文翻译：

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机器学习在顺序反卷积和卷积技术上的应用，用于分析核径迹检测器（NTD）的图像

提出了一种新颖的图像分析算法，该算法应用于核径迹探测器（NTD）的图像。与其他传统的图像分析技术相比，此过程涉及顺序应用去卷积和卷积技术，然后应用人工神经网络（ANN）来识别NTD中的蚀刻坑开口，从而获得了更高的成功率。