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English(EN) SINA: A Fully Automated Circuit Schematic Image to Netlist Generator Using Artificial Intelligence

AI工具SINA以96.67%的准确率自动化电路原理图到网表的转换

研究人员开发了SINA,一个开源工具,使用人工智能将电路原理图图像转换为机器可读的网表。该系统集成了深度学习用于元件检测,OCR用于文本提取,以及视觉-语言模型用于准确的参考标识符分配。SINA旨在通过处理集成电路和印刷电路板原理图,区分连接点和交叉导线,并实现96.67%的网表生成准确率,来克服当前方法的局限性。 AI

影响 该工具可以通过自动化一个先前手动且易出错的转换步骤,显著加速集成电路和印刷电路板的设计和仿真过程。

排序理由 该集群描述了一篇详细介绍基于AI的新系统用于特定技术任务的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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AI工具SINA以96.67%的准确率自动化电路原理图到网表的转换

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该集群描述了一篇详细介绍基于AI的新系统用于特定技术任务的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Saoud Aldowaish, Yashwanth Karumanchi, Kai-Chen Chiang, Mohammed Ayman Habib, Finn Murphy, Rishen Cao, Morteza Fayazi ·

    新浪:利用人工智能实现全自动电路原理图图像到网表生成器

    arXiv:2607.01609v1 Announce Type: new Abstract: Recent advances in Artificial Intelligence (AI) have revolutionized Electronic Design Automation (EDA), particularly through Large Language Models (LLMs) for circuit design tasks. However, their application to analog and mixed-signa…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    新浪:利用人工智能实现全自动电路原理图图像到网表生成器

    Recent advances in Artificial Intelligence (AI) have revolutionized Electronic Design Automation (EDA), particularly through Large Language Models (LLMs) for circuit design tasks. However, their application to analog and mixed-signal domains remains limited by the lack of machine…