{"id":"https://openalex.org/W4402194436","doi":"https://doi.org/10.1145/3670474.3685942","title":"ICDaIR: Distribution-aware Static IR Drop Prediction Flow Based on Image Classification","display_name":"ICDaIR: Distribution-aware Static IR Drop Prediction Flow Based on Image Classification","publication_year":2024,"publication_date":"2024-09-03","ids":{"openalex":"https://openalex.org/W4402194436","doi":"https://doi.org/10.1145/3670474.3685942"},"language":"en","primary_location":{"id":"doi:10.1145/3670474.3685942","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3670474.3685942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD","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/A5012049104","display_name":"Pinquan Li","orcid":"https://orcid.org/0009-0009-2196-4195"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pinquan Li","raw_affiliation_strings":["Southeast University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101296221","display_name":"Yunfan Zuo","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfan Zuo","raw_affiliation_strings":["Southeast University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101020818","display_name":"Yuwei Sun","orcid":"https://orcid.org/0009-0002-9587-0596"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Sun","raw_affiliation_strings":["Southeast University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040139371","display_name":"Hao Yan","orcid":"https://orcid.org/0000-0002-5312-4483"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Yan","raw_affiliation_strings":["Southeast University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101499715","display_name":"Longxing Shi","orcid":"https://orcid.org/0000-0002-0629-7154"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longxing Shi","raw_affiliation_strings":["Southeast University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012049104"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.2173,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49280976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9204000234603882,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.6849676370620728},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4828117787837982},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.454422265291214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42654505372047424},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42169368267059326},{"id":"https://openalex.org/keywords/drop","display_name":"Drop (telecommunication)","score":0.41048580408096313},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3589089512825012},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1202843189239502}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6849676370620728},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4828117787837982},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.454422265291214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42654505372047424},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42169368267059326},{"id":"https://openalex.org/C2781345722","wikidata":"https://www.wikidata.org/wiki/Q5308388","display_name":"Drop (telecommunication)","level":2,"score":0.41048580408096313},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3589089512825012},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1202843189239502},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3670474.3685942","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3670474.3685942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1598246754","https://openalex.org/W2014505173","https://openalex.org/W2161338410","https://openalex.org/W2996794321","https://openalex.org/W3013164405","https://openalex.org/W3015788359","https://openalex.org/W3116677748","https://openalex.org/W3127939301","https://openalex.org/W4280562550","https://openalex.org/W4295791104","https://openalex.org/W4297983935","https://openalex.org/W4381415966","https://openalex.org/W4386076377"],"related_works":["https://openalex.org/W2067708327","https://openalex.org/W2005525218","https://openalex.org/W1969952513","https://openalex.org/W2937289461","https://openalex.org/W1968145702","https://openalex.org/W4386850864","https://openalex.org/W2007417831","https://openalex.org/W2018261607","https://openalex.org/W2291489469","https://openalex.org/W2546503577"],"abstract_inverted_index":{"During":[0],"the":[1,6,19,24,88,106,112,125,129,141],"integrated":[2],"circuit":[3],"design":[4],"process,":[5],"maximum":[7,20,116],"IR":[8,21,45,89,99],"drop":[9,22,46,90,100],"value":[10],"is":[11,84,102],"often":[12],"given":[13],"more":[14],"attention.":[15],"The":[16,97],"frequency":[17],"of":[18,95,119,131],"in":[23,73],"actual":[25],"circuits":[26],"presents":[27],"an":[28],"uneven":[29],"dispersion,":[30],"i.e.,":[31],"long-tail":[32],"distribution.":[33],"To":[34],"address":[35],"this":[36,38],"problem,":[37],"paper":[39],"introduces":[40],"ICDaIR,":[41],"a":[42,56,80,115],"distribution-aware":[43],"static":[44],"prediction":[47,82,142],"flow":[48],"based":[49],"on":[50],"image":[51],"classification.":[52],"ICDaIR":[53],"first":[54],"utilizes":[55],"random":[57],"forest":[58],"classifier":[59],"to":[60,86],"categorize":[61],"sub-regions,":[62],"obtained":[63],"from":[64,108],"segmentation,":[65],"into":[66],"three":[67],"groups.":[68],"There":[69],"are":[70],"small":[71],"differences":[72],"sub-regional":[74],"samples":[75],"within":[76,145],"each":[77,93],"category.":[78],"Then,":[79],"U-Net-based":[81],"model":[83,126,133],"used":[85],"obtain":[87],"map":[91,101],"for":[92],"class":[94],"sub-region.":[96],"overall":[98],"derived":[103],"by":[104,135],"combining":[105],"values":[107],"these":[109],"sub-regions.":[110],"On":[111],"dataset":[113],"with":[114,122,140],"layout":[117],"area":[118],"0.69\u03bcm2,":[120],"compared":[121],"SOTA":[123],"and":[124,137],"without":[127],"classification,":[128],"MAE":[130],"our":[132],"decreases":[134],"50.5%":[136],"14.4%":[138],"respectively,":[139],"error":[143],"controlled":[144],"0.2029mV.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
