Hand-Drawn Circuit Schematic Digitization and Netlisting Using Machine Learning with Emphasis on Signal Integrity Applications

There is an emerging keen interest in the design and academic communities to automatically generate a simulatable netlist from hand-drawn schematics. This paper presents a novel machine learning-based circuit digitization and netlisting methodology.

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Publication Details

Published
2024-10-06
DOI
https://doi.org/10.1109/epeps61853.2024.10754479
Citations
3
Primary Topic
VLSI and Analog Circuit Testing
Type
article
Field-Weighted Citation Impact
1.47
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article

Hand-Drawn Circuit Schematic Digitization and Netlisting Using Machine Learning with Emphasis on Signal Integrity Applications

Ramachandra Achar, Anuj Mathur
3 citations
VLSI and Analog Circuit Testing
1.47
article

Hand-Drawn Circuit Schematic Digitization and Netlisting Using Machine Learning with Emphasis on Signal Integrity Applications

Ramachandra Achar, Anuj Mathur
article en
3 citations

Abstract

There is an emerging keen interest in the design and academic communities to automatically generate a simulatable netlist from hand-drawn schematics. This paper presents a novel machine learning-based circuit digitization and netlisting methodology.

Carleton University (CA)
Quality Education
Openalex Percentile: Top 16%
VLSI and Analog Circuit Testing
1.47
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