The DNN models of this technology include a LithoNet, an OPCNet,a layout novelty detection network. LithoNet is a learning-based pre-simulation model for layout-to-SEM contour prediction,OPCnet is a dual network of LithoNet for photomask optimization. Integrated with a well-trained LithoNet, our layout novelty detection network, consisting of a self-attention guided LithoNetan autoencoder, can check if there are layout patterns easily resulting in local distortions in contours of metal lines based on multi-modal (global-local) feature fusion.

This technique combines deep learningdigital twin technologies to connect the designconstruction processto achieve construction-site rebar inspection, issue tracking, verificationmaintenance. This core component of this method is based on the image collection of rebar frames, digital twin creation, cooperative machine learning,the rebar inspection module development. The BIM model was automatically matchedcompared with the 4D digital twin with features of point cloudtime sequence.