TY - GEN
T1 - Automatic Error Detection in Integrated Circuits Image Segmentation
T2 - 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
AU - Zhang, Zhikang
AU - Trindade, Bruno Mac Hado
AU - Green, Michael
AU - Yu, Zifan
AU - Pawlowicz, Christopher
AU - Ren, Fengbo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Due to the complicated nanoscale structures of current integrated circuits(IC) builds and low error tolerance of IC image segmentation tasks, most existing automated IC image segmentation approaches require human experts for visual inspection to ensure correctness, which is one of the major bottlenecks in large-scale industrial applications. In this paper, we present the first data-driven automatic error detection approach that targets two types of IC segmentation errors: wire and via errors. On an IC image dataset collected from real industry, we demonstrate that, by adapting existing CNN-based approaches of image classification and image translation with additional pre-processing and post-processing techniques, we are able to achieve recall/precision of 0.92/0.93 in wire error detection and 0.96/0.90 in via error detection, respectively.
AB - Due to the complicated nanoscale structures of current integrated circuits(IC) builds and low error tolerance of IC image segmentation tasks, most existing automated IC image segmentation approaches require human experts for visual inspection to ensure correctness, which is one of the major bottlenecks in large-scale industrial applications. In this paper, we present the first data-driven automatic error detection approach that targets two types of IC segmentation errors: wire and via errors. On an IC image dataset collected from real industry, we demonstrate that, by adapting existing CNN-based approaches of image classification and image translation with additional pre-processing and post-processing techniques, we are able to achieve recall/precision of 0.92/0.93 in wire error detection and 0.96/0.90 in via error detection, respectively.
KW - error detection
KW - image classification
KW - image segmentation
KW - image translation
KW - reverse engineering
UR - http://www.scopus.com/inward/record.url?scp=85177603563&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85177603563&partnerID=8YFLogxK
U2 - 10.1109/ICASSP49357.2023.10095703
DO - 10.1109/ICASSP49357.2023.10095703
M3 - Conference contribution
AN - SCOPUS:85177603563
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
BT - ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 June 2023 through 10 June 2023
ER -