Summary of Ai-guided Feature Segmentation Techniques to Model Features From Single Crystal Diamond Growth, by Rohan Reddy Mekala et al.
AI-Guided Feature Segmentation Techniques to Model Features from Single Crystal Diamond Growth
by Rohan Reddy Mekala, Elias Garratt, Matthias Muehle, Arjun Srinivasan, Adam Porter, Mikael Lindvall
First submitted to arxiv on: 10 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores machine learning approaches to optimize the growth of high-quality diamonds for various applications. The main challenge is extracting accurate spatial features from datasets that are time-dependent and have low volume but high complexity. A novel deep learning-driven approach, called semantic segmentation, isolates and classifies pixel masks of geometric features like diamond, pocket holder, and background. This approach uses an annotation-focused human-in-the-loop software architecture for training datasets, which reduces labeling time and cost while achieving high accuracy. The top-performing model, based on the DeeplabV3plus architecture, achieves excellent classification accuracy for various features of interest. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps scientists grow better diamonds for different uses like optics crystals or quantum detectors. Right now, it’s hard to extract useful information from data collected during diamond growth because there’s not much data and it’s very complex. The authors came up with a new way to use machine learning to find important features in the images of growing diamonds. This approach involves people helping machines learn by labeling certain parts of the images as “diamond,” “pocket holder,” or “background.” With this method, the machine can quickly and accurately identify these features. |
Keywords
» Artificial intelligence » Classification » Deep learning » Machine learning » Semantic segmentation
