SINA: A Circuit Schematic Image-to-Netlist Generator Using Artificial Intelligence

• URL: http://arxiv.org/abs/2601.22114v1
• Date: Thu, 29 Jan 2026 18:41:52 GMT
• Title: SINA: A Circuit Schematic Image-to-Netlist Generator Using Artificial Intelligence
• Abstract summary: SINA is an open-source, fully automated circuit schematic image-to-netlist generator.<n>In experiments, SINA achieves 96.47% overall netlist-generation accuracy, which is 2.72x higher than state-of-the-art approaches.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Current methods for converting circuit schematic images into machine-readable netlists struggle with component recognition and connectivity inference. In this paper, we present SINA, an open-source, fully automated circuit schematic image-to-netlist generator. SINA integrates deep learning for accurate component detection, Connected-Component Labeling (CCL) for precise connectivity extraction, and Optical Character Recognition (OCR) for component reference designator retrieval, while employing a Vision-Language Model (VLM) for reliable reference designator assignments. In our experiments, SINA achieves 96.47% overall netlist-generation accuracy, which is 2.72x higher than state-of-the-art approaches.

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