Nanofiber SEM Images for Automated Defect Detection

851.8 MB of Scanning Electron Microscope images of electrospun Polyacrylonitrile nanofibers, categorized for defect detection. The dataset was created by CAGRI YARDIMCI and last updated on 2026-04-28. It supports a deep learning framework for classifying fibers as Non-Defective, Slightly Defective, or Defective.

Use Cases

• Train image classification models based on the three defect categories (Non-Defective, Slightly Defective, Defective).
• Benchmark deep learning models for defect detection in material science imaging.
• Develop automated quality control systems for electrospun nanofiber manufacturing.

Strengths

• Dataset size is 851.8 MB, indicating a substantial collection of image data.
• Images are categorized into three specific defect classes, providing clear labels for supervised learning.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Images likely collected via Scanning Electron Microscope (SEM) as part of a study on electrospun nanofibers.

Freshness

Last updated 2026-04-28 07:17:11; freshness should be verified.