Nanofiber SEM Dataset

This study presents a deep learning-based framework for automated defect detection in electrospun Polyacrylonitrile (PAN) nanofibers using Scanning Electron Microscope (SEM) images. The proposed Nanofiber Classifier model is trained on a dataset consisting of three categories: Slightly Defective, Defective, Non-DefectiveThis repository contains the source code and dataset necessary to replicate the results of the research paper:"Automated Defect Classification of Electrospun Polyacrylonitrile Nanofibers via Deep Learning of SEM Images"本研究提出一种基于深度学习的框架，可借助扫描电子显微镜（SEM）图像实现静电纺丝聚丙烯腈（PAN）纳米纤维的自动化缺陷检测。所提出的纳米纤维分类器（Nanofiber Classifier）模型在涵盖三类样本的数据集上完成训练，这三个类别分别为：轻微缺陷、缺陷、无缺陷。本仓库包含复现该研究论文成果所需的源代码与数据集，论文标题为《基于SEM图像深度学习实现静电纺丝聚丙烯腈纳米纤维的自动化缺陷分类》。