# Circuit Diagram Retrieval Based on Hierarchical Circuit Graph Representation

arXiv: https://arxiv.org/abs/2503.11658 · HTML: https://mlsanity.com/paper/2503.11658/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 51 references that are in the map.
- First posted on arXiv 5 Feb 2025.

## Builds on (most cited first, 12 of 12)

- [Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection](https://mlsanity.com/paper/2006.04388/) (2020)
- [VarifocalNet: An IoU-aware Dense Object Detector](https://mlsanity.com/paper/2008.13367/) (2020)
- [Learning with Average Precision: Training Image Retrieval with a Listwise Loss](https://mlsanity.com/paper/1906.07589/) (2019)
- [GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning](https://mlsanity.com/paper/2005.00406/) (2020)
- [A Decade Survey of Content Based Image Retrieval using Deep Learning](https://mlsanity.com/paper/2012.00641/) (2020)
- [Deep Learning for Instance Retrieval: A Survey](https://mlsanity.com/paper/2101.11282/) (2021)
- [CktGNN: Circuit Graph Neural Network for Electronic Design Automation](https://mlsanity.com/paper/2308.16406/) (2023)
- [GNN4IP: Graph Neural Network for Hardware Intellectual Property Piracy Detection](https://mlsanity.com/paper/2107.09130/) (2021)
- [Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design](https://mlsanity.com/paper/2203.15913/) (2022)
- [A general approach for identifying hierarchical symmetry constraints for analog circuit layout](https://mlsanity.com/paper/2010.00051/) (2020)
- [PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks](https://mlsanity.com/paper/2005.02154/) (2020)
- [Graph Attention-Based Symmetry Constraint Extraction for Analog Circuits](https://mlsanity.com/paper/2312.14405/) (2023)

## Built on by (most cited first, 1 of 1)

- [SINA: A Fully Automated Circuit Schematic Image to Netlist Generator Using Artificial Intelligence](https://mlsanity.com/paper/2607.01609/) (2026)

## Abstract (arXiv)

In the domain of analog circuit design, the retrieval of circuit diagrams has drawn a great interest, primarily due to its vital role in the consultation of legacy designs and the detection of design plagiarism. Existing image retrieval techniques are adept at handling natural images, which converts images into feature vectors and retrieval similar images according to the closeness of these vectors. Nonetheless, these approaches exhibit limitations when applied to the more specialized and intricate domain of circuit diagrams. This paper presents a novel approach to circuit diagram retrieval by employing a graph representation of circuit diagrams, effectively reformulating the retrieval task as a graph retrieval problem. The proposed methodology consists of two principal components: a circuit diagram recognition algorithm designed to extract the circuit components and topological structure of the circuit using proposed GAM-YOLO model and a 2-step connected domain filtering algorithm, and a hierarchical retrieval strategy based on graph similarity and different graph representation methods for analog circuits. Our methodology pioneers the utilization of graph representation in the retrieval of circuit diagrams, incorporating topological features that are commonly overlooked by standard image retrieval methods. The results of our experiments substantiate the efficacy of our approach in retrieving circuit diagrams across of different types.