Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation
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TL;DR - SFgen uses multimodal LLM agents to recognize and generate PCB component symbols and footprints, reducing reliance on error-prone manual library creation. It also powers SFnet, an expanding database currently covering 1,000 components.
- SFgen reports 86% accuracy for symbol generation.
- Footprint generation achieves 80% accuracy.
- The resulting SFnet database supports future automated PCB design generation.
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Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation
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Semantic Scholar citations 0 · Semantic Scholar influential citations 0
TL;DR - SFgen uses multimodal LLM agents to recognize and generate PCB component symbols and footprints, reducing reliance on error-prone manual library creation. It also powers SFnet, an expanding database currently covering 1,000 components.
- SFgen reports 86% accuracy for symbol generation.
- Footprint generation achieves 80% accuracy.
- The resulting SFnet database supports future automated PCB design generation.