IC SYNTHLOGO

IC SYNTHLOGO

Description The IC SynthLogo dataset is a synthetic image dataset created to enhance the detection of counterfeit and recycled Integrated Circuits (ICs) in Printed Circuit Boards (PCBs). It utilizes a novel automatic method to generate synthetic logo images of ICs, combining existing and newly developed techniques tailored for IC and PCB textures and colors. This dataset is particularly useful in evaluating the reliability and quality of counterfeit detection algorithms and aids in PCB marking detection. The dataset, along with scripts for creating images and their bounding box annotations, is available for training logo identification neural networks and machine learning algorithms. The dataset addresses the limitations of existing datasets in PCB assurance and hardware security, providing a valuable resource for training deep learning models in this field.
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Mukhil Azhagan Mallaiyan Sathiaseelan, Olivia P. Paradis, Rajat Rai, Suryaprakash Vasudev Pandurangi, Manoj Yasaswi Vutukuru, Shayan Taheri, Navid Asadizanjani; October 31–November 4, 2021. "Logo Classification and Data Augmentation Techniques for PCB Assurance and Counterfeit Detection." Proceedings of the ISTFA 2021. ISTFA 2021: Conference Proceedings from the 47th International Symposium for Testing and Failure Analysis. Phoenix, Arizona, USA. (pp. pp. 12-19). ASM. https://doi.org/10.31399/asm.cp.istfa2021p0012 @INPROCEEDINGS{9617352, author={Mallaiyan Sathiaseelan, Mukhil Azhagan and Vutukuru, Manoj Yasaswi and Pandurangi, Suryaprakash Vasudev and Taheri, Shayan and Asadizanjani, Navid}, booktitle={2021 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)}, title={IC SynthLogo: A Synthetic Logo Image Dataset for Counterfeit and Recycled IC detection}, year={2021}, volume={}, number={}, pages={1-8}, doi={10.1109/IPFA53173.2021.9617352}}