{"id":"https://openalex.org/W3011227197","doi":"https://doi.org/10.1145/3372780.3375565","title":"TEMPO: Fast Mask Topography Effect Modeling with Deep Learning","display_name":"TEMPO: Fast Mask Topography Effect Modeling with Deep Learning","publication_year":2020,"publication_date":"2020-03-20","ids":{"openalex":"https://openalex.org/W3011227197","doi":"https://doi.org/10.1145/3372780.3375565","mag":"3011227197"},"language":"en","primary_location":{"id":"doi:10.1145/3372780.3375565","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372780.3375565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Symposium on Physical Design","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077883798","display_name":"Wei Ye","orcid":"https://orcid.org/0000-0002-6768-967X"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wei Ye","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038501242","display_name":"Mohamed Baker Alawieh","orcid":"https://orcid.org/0000-0002-3546-0336"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed Baker Alawieh","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073713451","display_name":"Yuki Watanabe","orcid":"https://orcid.org/0000-0003-2708-9191"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuki Watanabe","raw_affiliation_strings":["Kioxia Corporation, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Kioxia Corporation, Yokohama, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037815960","display_name":"Shigeki Nojima","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shigeki Nojima","raw_affiliation_strings":["Kioxia Corporation, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Kioxia Corporation, Yokohama, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000933188","display_name":"Yibo Lin","orcid":"https://orcid.org/0000-0002-0977-2774"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Lin","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011883763","display_name":"David Z. Pan","orcid":"https://orcid.org/0000-0002-5705-2501"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Z. Pan","raw_affiliation_strings":["University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5077883798"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":1.5412,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.82553453,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"127","last_page":"134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7263825535774231},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.7049317359924316},{"id":"https://openalex.org/keywords/lithography","display_name":"Lithography","score":0.5889514684677124},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5705217719078064},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.543937087059021},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5346720814704895},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45690977573394775},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45190727710723877},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4499198794364929},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43620193004608154},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4179079532623291},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.41577377915382385},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.35695940256118774},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33278268575668335},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33060500025749207},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11257737874984741},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10811388492584229},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.09760671854019165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7263825535774231},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.7049317359924316},{"id":"https://openalex.org/C204223013","wikidata":"https://www.wikidata.org/wiki/Q133036","display_name":"Lithography","level":2,"score":0.5889514684677124},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5705217719078064},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.543937087059021},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5346720814704895},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45690977573394775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45190727710723877},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4499198794364929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43620193004608154},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4179079532623291},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.41577377915382385},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.35695940256118774},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33278268575668335},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33060500025749207},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11257737874984741},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10811388492584229},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.09760671854019165},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3372780.3375565","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372780.3375565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Symposium on Physical Design","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W589621558","https://openalex.org/W1566629850","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W2018890340","https://openalex.org/W2021936167","https://openalex.org/W2053066651","https://openalex.org/W2060214472","https://openalex.org/W2069763279","https://openalex.org/W2070275556","https://openalex.org/W2099471712","https://openalex.org/W2105559484","https://openalex.org/W2114667122","https://openalex.org/W2125389028","https://openalex.org/W2137057062","https://openalex.org/W2150099050","https://openalex.org/W2156106583","https://openalex.org/W2173520492","https://openalex.org/W2173692178","https://openalex.org/W2492136742","https://openalex.org/W2523714292","https://openalex.org/W2741728759","https://openalex.org/W2768626898","https://openalex.org/W2842482802","https://openalex.org/W2913204915","https://openalex.org/W2945764596","https://openalex.org/W2949117887","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963344645","https://openalex.org/W2963470893","https://openalex.org/W2963684088","https://openalex.org/W2963767194","https://openalex.org/W2964309037","https://openalex.org/W2996886069","https://openalex.org/W6678815747"],"related_works":["https://openalex.org/W2058561567","https://openalex.org/W2062441160","https://openalex.org/W1981376670","https://openalex.org/W2021096143","https://openalex.org/W2053176790","https://openalex.org/W1971370789","https://openalex.org/W2036786079","https://openalex.org/W1991287413","https://openalex.org/W2001376103","https://openalex.org/W1712733447"],"abstract_inverted_index":{"With":[0],"the":[1,5,15,19,26,93,112,117,124,131],"continuous":[2],"shrinking":[3],"of":[4,82,96,109],"semiconductor":[6],"device":[7],"dimensions,":[8],"mask":[9,42],"topography":[10,43],"effects":[11,24,44],"stand":[12],"out":[13],"among":[14,134],"major":[16],"factors":[17],"influencing":[18],"lithography":[20,27],"process.":[21],"Including":[22],"these":[23],"in":[25,127,139,148],"optimization":[28],"procedure":[29],"has":[30],"become":[31],"necessary":[32],"for":[33,41,49,64,101],"advanced":[34],"technology":[35],"nodes.":[36],"However,":[37],"conventional":[38],"rigorous":[39,169],"simulation":[40,170],"is":[45],"extremely":[46],"computationally":[47],"expensive":[48],"high":[50],"accuracy.":[51,174],"In":[52,121],"this":[53,122],"work,":[54],"we":[55],"propose":[56],"TEMPO":[57,75,105,128,160],"as":[58,107],"a":[59,77,98],"novel":[60],"generative":[61,78],"learning-based":[62],"framework":[63],"efficient":[65],"and":[66,152],"accurate":[67],"3D":[68],"aerial":[69,84,119],"image":[70,85],"prediction.":[71],"At":[72],"its":[73,110],"core,":[74],"comprises":[76],"adversarial":[79],"network":[80],"capable":[81],"predicting":[83],"intensity":[86],"at":[87],"different":[88,135],"resist":[89],"heights.":[90],"Compared":[91],"to":[92,115,164],"default":[94],"approach":[95],"building":[97],"unique":[99],"model":[100,126,141,150],"each":[102],"desired":[103,113],"height,":[104],"takes":[106],"one":[108],"inputs":[111],"height":[114],"produce":[116],"corresponding":[118],"image.":[120],"way,":[123],"global":[125],"can":[129,161],"capture":[130],"shared":[132],"behavior":[133],"heights,":[136],"thus,":[137],"resulting":[138],"smaller":[140],"size.":[142],"Besides,":[143],"across-height":[144],"information":[145],"sharing":[146],"results":[147,157],"better":[149],"accuracy":[151],"generalization":[153],"capability.":[154],"Our":[155],"experimental":[156],"demonstrate":[158],"that":[159],"obtain":[162],"up":[163],"1170x":[165],"speedup":[166],"compared":[167],"with":[168],"while":[171],"achieving":[172],"satisfactory":[173]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}