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Image-based model enhances the detection of surface defects in low-light industrial settings
In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...
Chipmakers worldwide consider Automatic Test Pattern Generation (ATPG) their go-to method for achieving high test coverage in production. ATPG generates test patterns designed to detect faults in the ...
Industrial automation is moving beyond rigid rule-based control systems toward environments where machines can interpret ...
The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well-suited ...
This article is adapted from a presentation at TestConX, March 5-8, 2023, Mesa, AZ, by Vijayakumar Thangamariappan, Nidhi Agrawal, Jason Kim, Constantinos Xanthopoulos, Ira Leventhal, and Ken Butler, ...
The Industrial Science Report: AI reshapes productivity, sustainability, and supply chain resilience
AI is becoming core infrastructure in manufacturing, accelerating process optimization, reducing waste, and enabling faster, ...
Researchers have designed a robust image-based anomaly detection (AD) framework with illumination enhancement and noise suppression features that can enhance the detection of subtle defects in ...
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