AI-Guided Feature Segmentation Techniques to Model Features from Single Crystal Diamond Growth

arXiv:2404.08017v1 Announce Type: new
Abstract: Process refinement to consistently produce high-quality material over a large area of the grown crystal, enabling various applications from optics crystals to quantum detectors, has long been a goal for diamond growth. Machine learning offers a promising path toward this goal, but faces challenges such as the complexity of features within datasets, their time-dependency, and the volume of data produced per growth run. Accurate spatial feature extraction from image to image for real-time monitoring of …

abstract applications arxiv cs.ai cs.cv detectors enabling feature features growth machine machine learning material optics path process quality quantum segmentation type