Many-Layer Hotspot Detection by Layer-Attentioned Visual Question Answering
Yen-Shuo Chen1 and Iris Hui-Ru Jiang1,2
1Department of Electrical Engineering, National Taiwan University, Taipei 10617, Taiwan
spwqee21@gmail.com
2Graduate Institute of Electronics Engineering, National Taiwan University, Taipei 10617, Taiwan
huiru.jiang@gmail.com
ABSTRACT
Exploring hotspot patterns and correcting them as early as possible is crucial to guarantee yield and manufacturability. Existing hotspot detection and pattern classification methods consider only the geometry on one single layer or one main layer with adjacent layers. In this paper, we investigate the linkage between many-layer hotspot patterns and potentially induced defect types. We first cast the many-layer critical hotspot pattern extraction task as a visual question answering (VQA) problem: Considering a many-layer layout pattern an image and a defect type a question, we devise a layer-attentioned VQA model to answer whether the pattern is critical to the queried defect type. Furthermore, our layer attention mechanism attempts to identify the relevance of each layer for different defect types. Experimental results demonstrate that the proposed model has superior question-answering ability for modern layouts with more than thirty layout layers.
