Printed electronics (PE) circuits have several advantages over silicon counterparts for the applications where mechanical flexibility, extremely low-cost, large area, and custom fabrication are required. The custom (personalized) fabrication is a key feature of this technology, enabling customization per application, even in small quantities due to low-cost printing compared with lithography. However, the personalized and on-demand fabrication, the non-standard circuit design, and the limited number of printing layers with larger geometries compared with traditional silicon chip manufacturing open doors for new and unique reverse engineering (RE) schemes for this technology. In this paper, we present a robust RE methodology based on supervised machine learning, starting from image acquisition all the way to netlist extraction. The results show that the proposed RE methodology can reverse engineer the PE circuits with very limited manual effort and is robust against non-standard circuit design, customized layouts, and high variations resulting from the inherent properties of PE manufacturing processes.

中文翻译：

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印刷电子电路的逆向工程：从成像到网表提取


对于需要机械灵活性、极低成本、大面积和定制制造的应用，印刷电子 (PE) 电路比硅电路具有多种优势。定制（个性化）制造是该技术的一个关键特征，由于与光刻相比印刷成本较低，因此即使是小批量，也可以根据应用进行定制。然而，与传统硅芯片制造相比，个性化和按需制造、非标准电路设计以及有限数量的具有较大几何形状的印刷层为该技术的新的和独特的逆向工程（RE）方案打开了大门。在本文中，我们提出了一种基于监督机器学习的强大 RE 方法，从图像采集一直到网表提取。结果表明，所提出的 RE 方法可以通过非常有限的手动工作对 PE 电路进行逆向工程，并且对于非标准电路设计、定制布局以及 PE 制造工艺的固有属性导致的高变化具有鲁棒性。