Deep learning makes X-ray CT inspection of 3D-printed parts faster, more accurate Date: October 14, 2022 Source: DOE/Oak Ridge National Laboratory Summary: A new deep-learning framework is ...

The AttendSeg deep learning model performs semantic segmentation at an accuracy that is almost on-par with RefineNet while cutting down the number of parameters to 1.19 million.

Thus, the growing demand for 3D IC has generated considerable attention on the importance of reliability analysis and failure prediction. This research conducts 3D X-ray tomographic images combining ...

Deep learning (DL) methods have shown remarkable successes in medical image segmentation, often using large amounts of annotated data for model training. However, acquiring a large number of diverse ...

He K, Zhang X, Ren S, Sun J. Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2016) p. 770–8. doi: 10.1109/CVPR.2016.90 ...

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A new deep-learning framework developed at the Department of Energy’s Oak Ridge National Laboratory is speeding up the process of inspecting additively manufactured metal parts using X-ray ...