• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.208-215
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• 2016

The lithography hotspot detection process is crucial for semiconductor design development process. But, the lithography hotspot detection using optical simulation method takes much time and it slowdown the layout design development cycle. Though the geometry based approach is introduced as an alternative, it still revealed low detection performance and sophisticated framework. To solve this problem, we introduce a deep convolutional neural network based hotspot detection method. Our method made better results in ICCCAD 2012 dataset. To reach this score, we used lots of technical effort to improve the result in addition to just utilizing the nature of convolutional neural network. Inspection region reduction, data augmentation, DBSCAN clustering helped our work more stable and faster.