mlsanityData to 7 Oct 2026

SSGD: A smartphone screen glass dataset for defect detection

arXiv 2303.06673 ↗First posted 12 Mar 2023cs.CV cs.AIcited by 5

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Abstract (arXiv)

Interactive devices with touch screen have become commonly used in various aspects of daily life, which raises the demand for high production quality of touch screen glass. While it is desirable to develop effective defect detection technologies to optimize the automatic touch screen production lines, the development of these technologies suffers from the lack of publicly available datasets. To address this issue, we in this paper propose a dedicated touch screen glass defect dataset which includes seven types of defects and consists of 2504 images captured in various scenarios.All data are captured with professional acquisition equipment on the fixed workstation. Additionally, we benchmark the CNN- and Transformer-based object detection frameworks on the proposed dataset to demonstrate the challenges of defect detection on high-resolution images. Dataset and related code will be available at https://github.com/Yangr116/SSGDataset.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 16 of its 24 references that are in the map. First posted on arXiv 12 Mar 2023.

Builds on

16 of 24 references.

References · 16

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4 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 0; 2025: 1; 2026: 1.

5 papers.

  1. 2023GPT4Tools: Teaching Large Language Model to Use Tools via Self-instructioncited by 245
  2. 2023Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Reviewcited by 17
  3. 2023XIMAGENET-12: An Explainable AI Benchmark Dataset for Model Robustness Evaluationcited by 2
  4. 2025Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environmentscited by 0
  5. 2026Multi-View Reflective Surface Inspection via Semantic-Saliency Cross-Verificationcited by 0