Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on pattern recognition and artificial intelligence are presented in a new report. According to news reporti ng out of National Taiwan University of Science and Technology by NewsRx editors , research stated, “Defect detection is a crucial technology that is extensively employed in the manufacturing industry to monitor and ensure the quality of out put. Deep learning models have shown remarkable potential for defect detection.”Our news reporters obtained a quote from the research from National Taiwan Unive rsity of Science and Technology: “However, the success of these models heavily r elies on voluminous training data. Collecting substantial amounts of defect data is challenging in practical settings, and the tedious process of pixel-level de fect annotation further complicates the task. Among the common defects encounter ed in manufacturing, scratches are particularly significant. To address these ch allenges, this study proposes a two-phase generative adversarial network (GAN) a pproach for synthesizing defect images and generating semi-automatic pixel-wise labels for anomaly detection. The first phase primarily focuses on synthesizing images, while the second phase involves the pixel-wise labeling of the images. T he synthesized paired images generated by the GANs serve as input to the semanti c network.”
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