用YOLO模型实现硅光芯片光束的实时检测与自动对焦
Real-time Detection and Auto focusing of Beam Profiles from Silicon Photonics Gratings using YOLO model
- 基于YOLO模型实现光束图像自动识别与定位
- 检测准确率达99.7%，置信度超0.95，支持实时计算光束宽度
- 适合硅光芯片测试、自动化光学调试场景
在观察硅光芯片（SiPh）向自由空间发射的光束时，常需手动调节相机镜头以获得清晰成像。本文展示了一种基于你只看一次（YOLO）模型的自动对焦系统。训练后的YOLO模型在检测SiPh光栅出射光束时表现出99.7%的高分类准确率和>0.95的高置信度。文中还提供了实时光束检测、实时光束宽度计算及自动对焦的视频演示。
原文摘要 · Abstract (English)
When observing the chip-to-free-space light beams from silicon photonics (SiPh) to free-space, manual adjustment of camera lens is often required to obtain a focused image of the light beams. In this letter, we demonstrated an auto-focusing system based on you-only-look-once (YOLO) model. The trained YOLO model exhibits high classification accuracy of 99.7% and high confidence level >0.95 when detecting light beams from SiPh gratings. A video demonstration of real-time light beam detection, real-time computation of beam width, and auto focusing of light beams are also included.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。