{"id":"https://openalex.org/W2183341477","doi":"https://doi.org/10.1109/cvpr.2016.308","title":"Rethinking the Inception Architecture for Computer Vision","display_name":"Rethinking the Inception Architecture for Computer Vision","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2183341477","doi":"https://doi.org/10.1109/cvpr.2016.308","mag":"2183341477"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2016.308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2016.308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5002183320","display_name":"Christian Szegedy","orcid":"https://orcid.org/0000-0003-4295-1851"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Christian Szegedy","raw_affiliation_strings":["Google Inc"],"affiliations":[{"raw_affiliation_string":"Google Inc","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013813527","display_name":"Vincent Vanhoucke","orcid":"https://orcid.org/0000-0003-0544-2791"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vincent Vanhoucke","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032800189","display_name":"Sergey Ioffe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergey Ioffe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076054799","display_name":"Jon Shlens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jon Shlens","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041722253","display_name":"Zbigniew Wojna","orcid":"https://orcid.org/0000-0002-9629-5688"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zbigniew Wojna","raw_affiliation_strings":["University College London"],"affiliations":[{"raw_affiliation_string":"University College London","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5002183320"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":909.4414,"has_fulltext":false,"cited_by_count":30467,"citation_normalized_percentile":{"value":0.99996703,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2818","last_page":"2826"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8285741806030273},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5700426697731018},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.564075231552124},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5372236967086792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5062064528465271},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5050130486488342},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4865938425064087},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47667908668518066},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.45274221897125244},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4457218050956726},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4416995942592621},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.41950464248657227},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.35042616724967957},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21858108043670654}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8285741806030273},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5700426697731018},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.564075231552124},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5372236967086792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5062064528465271},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5050130486488342},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4865938425064087},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47667908668518066},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.45274221897125244},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4457218050956726},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4416995942592621},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.41950464248657227},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.35042616724967957},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21858108043670654},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2016.308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2016.308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W104184427","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1815076433","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1944396096","https://openalex.org/W2016053056","https://openalex.org/W2068730032","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2111979893","https://openalex.org/W2113325037","https://openalex.org/W2117539524","https://openalex.org/W2118097920","https://openalex.org/W2163605009","https://openalex.org/W2168894214","https://openalex.org/W2172166488","https://openalex.org/W2172654076","https://openalex.org/W3099206234","https://openalex.org/W6604254268","https://openalex.org/W6638667902","https://openalex.org/W6677907805","https://openalex.org/W6684191040","https://openalex.org/W6685405536"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2950871388","https://openalex.org/W2063781796"],"abstract_inverted_index":{"Convolutional":[0],"networks":[1,24,91],"are":[2,68,85],"at":[3,96],"the":[4,98,117,128,131,183,191],"core":[5],"of":[6,17,130,150,167],"most":[7,50],"state":[8,129],"of-the-art":[9],"computer":[10],"vision":[11,79],"solutions":[12],"for":[13,49,60,72,139],"a":[14,144,147],"wide":[15],"variety":[16],"tasks.":[18],"Since":[19],"2014":[20],"very":[21],"deep":[22],"convolutional":[23],"started":[25],"to":[26,43,45,88],"become":[27],"mainstream,":[28],"yielding":[29],"substantial":[30,125],"gains":[31,48,126],"in":[32,92],"various":[33,73],"benchmarks.":[34],"Although":[35],"increased":[36],"model":[37],"size":[38],"and":[39,64,80,109,135,156,170,178,186],"computational":[40,62,148],"cost":[41,149],"tend":[42],"translate":[44],"immediate":[46],"quality":[47],"tasks":[51],"(as":[52],"long":[53],"as":[54,77,101,103],"enough":[55],"labeled":[56],"data":[57],"is":[58],"provided":[59],"training),":[61],"efficiency":[63],"low":[65],"parameter":[66],"count":[67],"still":[69],"enabling":[70],"factors":[71],"use":[74],"cases":[75],"such":[76],"mobile":[78],"big-data":[81],"scenarios.":[82],"Here":[83],"we":[84,173],"exploring":[86],"ways":[87,93],"scale":[89],"up":[90],"that":[94],"aim":[95],"utilizing":[97],"added":[99],"computation":[100],"efficiently":[102],"possible":[104],"by":[105],"suitably":[106],"factorized":[107],"convolutions":[108],"aggressive":[110],"regularization.":[111],"We":[112],"benchmark":[113],"our":[114],"methods":[115],"on":[116,182,190],"ILSVRC":[118],"2012":[119],"classification":[120],"challenge":[121],"validation":[122,184],"set":[123,185],"demonstrate":[124],"over":[127],"art:":[132],"21:2%":[133],"top-1":[134,180],"5:6%":[136],"top-5":[137,176,188],"error":[138,177,181,189],"single":[140],"frame":[141],"evaluation":[142],"using":[143,158],"network":[145],"with":[146,157],"5":[151],"billion":[152],"multiply-adds":[153],"per":[154],"inference":[155],"less":[159],"than":[160],"25":[161],"million":[162],"parameters.":[163],"With":[164],"an":[165],"ensemble":[166],"4":[168],"models":[169],"multi-crop":[171],"evaluation,":[172],"report":[174],"3:5%":[175],"17:3%":[179],"3:6%":[187],"official":[192],"test":[193],"set.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":435},{"year":2025,"cited_by_count":2967},{"year":2024,"cited_by_count":3756},{"year":2023,"cited_by_count":4377},{"year":2022,"cited_by_count":4335},{"year":2021,"cited_by_count":5026},{"year":2020,"cited_by_count":4182},{"year":2019,"cited_by_count":3092},{"year":2018,"cited_by_count":1682},{"year":2017,"cited_by_count":532},{"year":2016,"cited_by_count":76},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}