Advancing X-ray Inspection with Deep Learning De-noising Technology

Sara Ziliani
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Abstract

X-ray inspection plays a pivotal role in the food and non-destructive testing industries, ensuring optimal products quality and safety. To improve contaminants and defects detection, it is crucial to reduce the amount of noise in the acquired images. Addressing this, Hamamatsu Photonics has developed a new de-noising technology based on deep learning algorithms and an innovative X-ray simulation method.
利用深度学习去噪技术推进 X 射线检测工作
X 射线检测在食品和无损检测行业中发挥着举足轻重的作用,可确保最佳的产品质量和安全。为了改进污染物和缺陷检测,减少采集图像中的噪声量至关重要。为此,Hamamatsu Photonics 开发了一种基于深度学习算法和创新 X 射线模拟方法的新型去噪技术。
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