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Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation

  • Yichen Shi
  • , Yuzhi Liu
  • , Zhuofu Tao
  • , Li Huang
  • , Yuhao Gao
  • , Ting Jung Lin*
  • , Lei He*
  • *Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

A rich and recognizable component library is the cornerstone of printed circuit board (PCB) design and generation. Traditionally, engineers manually create symbols and footprints and design PCB schematics, which is time-consuming and error-prone. Leveraging multimodal large language models (MLLMs), we develop SFgen, an agentic recognition and generation flow of symbol and footprint for electronic components. SFgen achieves 86% accuracy for symbol generation and 80% accuracy for footprint generation. We use the SFgen method to create SFnet, a database of symbols and footprints. It now has 1000 components and is expanding constantly, which lays the foundation for automatic generation of PCB designs.

Original languageEnglish
Title of host publicationPattern Recognition and Computer Vision - 8th Chinese Conference, PRCV 2025, Proceedings
EditorsJosef Kittler, Hongkai Xiong, Weiyao Lin, Jian Yang, Xilin Chen, Jiwen Lu, Jingyi Yu, Weishi Zheng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages65-78
Number of pages14
ISBN (Print)9789819556755
DOIs
Publication statusPublished - 2026
Externally publishedYes
Event8th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2025 - Shanghai, China
Duration: 15 Oct 202518 Oct 2025

Publication series

NameLecture Notes in Computer Science
Volume16278 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2025
Country/TerritoryChina
CityShanghai
Period15/10/2518/10/25

Free Keywords

  • Footprint
  • MLLM
  • PCB design
  • Symbol

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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