Post-layout wiring violation prediction method based on deep learning and readable storage medium
The invention discloses a post-layout wiring violation prediction method based on deep learning and a readable storage medium, and the method comprises the steps: segmenting first layout information according to preset windows, so as to obtain first feature information corresponding to each preset w...
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creator | LI NAN ZHANG XI FAN QINCHUN |
description | The invention discloses a post-layout wiring violation prediction method based on deep learning and a readable storage medium, and the method comprises the steps: segmenting first layout information according to preset windows, so as to obtain first feature information corresponding to each preset window; obtaining a first feature image corresponding to each piece of first feature information according to the first feature information; obtaining a first five-dimensional tensor image according to all the first feature images corresponding to the same preset window; obtaining a corresponding first design rule violation image according to a preset window; obtaining a trained first network model; obtaining a first training model based on the trained first network model; obtaining a second training model; obtaining a final training model; and inputting the to-be-predicted data into the final training model to obtain a prediction result. According to the method, the layout can be adjusted intime under the condition |
format | Patent |
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According to the method, the layout can be adjusted intime under the condition</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNi0EKwjAQRbtxIeodxgN0kRYPIEVxJS7cl2nnWwNpJiSp4u2t4gFcvf_gv2XBF025dPzSKdPTRusHelh1nK16ChFi--8cke8q1HGC0OwCBHLg6D8Je6EIFu4cKGWNPGBOxE7juljc2CVsflwV2-Ph2pxKBG2RAvfwyG1zNqaq6tqY3b7-5_MGPw492Q</recordid><startdate>20210115</startdate><enddate>20210115</enddate><creator>LI NAN</creator><creator>ZHANG XI</creator><creator>FAN QINCHUN</creator><scope>EVB</scope></search><sort><creationdate>20210115</creationdate><title>Post-layout wiring violation prediction method based on deep learning and readable storage medium</title><author>LI NAN ; ZHANG XI ; FAN QINCHUN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN112233115A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>LI NAN</creatorcontrib><creatorcontrib>ZHANG XI</creatorcontrib><creatorcontrib>FAN QINCHUN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LI NAN</au><au>ZHANG XI</au><au>FAN QINCHUN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Post-layout wiring violation prediction method based on deep learning and readable storage medium</title><date>2021-01-15</date><risdate>2021</risdate><abstract>The invention discloses a post-layout wiring violation prediction method based on deep learning and a readable storage medium, and the method comprises the steps: segmenting first layout information according to preset windows, so as to obtain first feature information corresponding to each preset window; obtaining a first feature image corresponding to each piece of first feature information according to the first feature information; obtaining a first five-dimensional tensor image according to all the first feature images corresponding to the same preset window; obtaining a corresponding first design rule violation image according to a preset window; obtaining a trained first network model; obtaining a first training model based on the trained first network model; obtaining a second training model; obtaining a final training model; and inputting the to-be-predicted data into the final training model to obtain a prediction result. According to the method, the layout can be adjusted intime under the condition</abstract><oa>free_for_read</oa></addata></record> |
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language | chi ; eng |
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subjects | CALCULATING COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
title | Post-layout wiring violation prediction method based on deep learning and readable storage medium |
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