Deep Learning-Enabled Visual Inspection of Gap Spacing in High-Precision Equipment: A Comparative Study

Machines, Journal Year: 2025, Volume and Issue: 13(2), P. 74 - 74

Published: Jan. 21, 2025

In the realm of industrial quality control, visual inspection plays a pivotal role in ensuring product precision and consistency. Moreover, it enables non-contact inspection, preventing products from potential damage, timely monitoring capabilities facilitate quick decision making. However, traditional methods, such as manual using feeler gauges, are time-consuming, labor-intensive, prone to human error. To address these limitations, this study proposes deep learning-based system for measuring gap spacing high-precision equipment. Utilizing DeepLSD algorithm, integrates learning techniques enhance line segment detection, resulting more robust accurate outcomes. Key performance improvements were realized, with proposed being piece learning-enabled mobile equipment inspecting real-time. Through comparative analysis gauge method, demonstrated significant time, accuracy, user experience, while reducing workload. Experimental results validate effectiveness efficiency approach, highlighting its widespread application activities.

Language: Английский

ShuffleTransformerMulti-headAttentionNet network for user load forecasting

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135537 - 135537

Published: March 1, 2025

Language: Английский

Edge Grading in Trading Cards Using Transfer Learning: Methods, Experiments, and Evaluation

2021 IEEE International Conference on Big Data (Big Data), Journal Year: 2024, Volume and Issue: unknown, P. 2005 - 2012

Published: Dec. 15, 2024

Language: Английский