光学
机器视觉
变压器
激光束
人工智能
计算机科学
模式识别(心理学)
计算机视觉
电子工程
工程类
电气工程
物理
电压
激光器
作者
Yu Dian Lim,Chuan Seng Tan
标识
DOI:10.1109/jlt.2025.3537677
摘要
A vision transformer (ViT) is developed to perform beam profile classification on beam profiles coupled out from silicon photonics (SiPh) gratings. The classification task is aimed to distinguish ‘focused’ and ‘sparse’ beam profiles, and the regions where the corresponding beam profiles are located above the SiPh gratings. Upon training with 1247 beam profile, the ViT model is able to perform 6-category classification task on 832 beam profiles with classification accuracy of 0.978. Since the training of ViT is probabilistic in nature, the ViT training is repeated for 200 times to test its robustness. Classification accuracy ranges from 0.952 to 0.981 is obtained.
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