{"id":"https://openalex.org/W3202546765","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534219","title":"Do CNNs Encode Data Augmentations?","display_name":"Do CNNs Encode Data Augmentations?","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3202546765","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534219","mag":"3202546765"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5000435983","display_name":"Eddie Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eddie Yan","raw_affiliation_strings":["NVIDIA,Santa Clara,USA","NVIDIA, Santa Clara, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA,Santa Clara,USA","institution_ids":["https://openalex.org/I4210127875"]},{"raw_affiliation_string":"NVIDIA, Santa Clara, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033809109","display_name":"Yanping Huang","orcid":"https://orcid.org/0000-0002-4430-3965"},"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":false,"raw_author_name":"Yanping Huang","raw_affiliation_strings":["Google Brain,Mountain View,USA","Google Brain, Mountain View, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Brain,Mountain View,USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Brain, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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":0.9993000030517578,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9983999729156494,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.998199999332428,"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/encode","display_name":"ENCODE","score":0.8867557644844055},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7431524991989136},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6810851693153381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6528107523918152},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4697330892086029},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4577125906944275},{"id":"https://openalex.org/keywords/hue","display_name":"Hue","score":0.4388082027435303},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41254886984825134}],"concepts":[{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.8867557644844055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7431524991989136},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6810851693153381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6528107523918152},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4697330892086029},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4577125906944275},{"id":"https://openalex.org/C126537357","wikidata":"https://www.wikidata.org/wiki/Q372948","display_name":"Hue","level":2,"score":0.4388082027435303},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41254886984825134},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":75,"referenced_works":["https://openalex.org/W252252322","https://openalex.org/W1800922288","https://openalex.org/W1849277567","https://openalex.org/W1945616565","https://openalex.org/W2108598243","https://openalex.org/W2141125852","https://openalex.org/W2142697503","https://openalex.org/W2158485497","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2279221249","https://openalex.org/W2295107390","https://openalex.org/W2553303224","https://openalex.org/W2618530766","https://openalex.org/W2746314669","https://openalex.org/W2765407302","https://openalex.org/W2785397276","https://openalex.org/W2789942385","https://openalex.org/W2891364477","https://openalex.org/W2913314773","https://openalex.org/W2949736877","https://openalex.org/W2953384591","https://openalex.org/W2955425717","https://openalex.org/W2962790223","https://openalex.org/W2962851944","https://openalex.org/W2962858109","https://openalex.org/W2963108767","https://openalex.org/W2963207607","https://openalex.org/W2963239066","https://openalex.org/W2964193438","https://openalex.org/W2965658867","https://openalex.org/W2971315489","https://openalex.org/W2976638463","https://openalex.org/W2978426779","https://openalex.org/W2982238751","https://openalex.org/W2992308087","https://openalex.org/W2995360807","https://openalex.org/W2995426144","https://openalex.org/W3003926725","https://openalex.org/W3023215041","https://openalex.org/W3035160371","https://openalex.org/W3035743198","https://openalex.org/W3039817009","https://openalex.org/W3104962541","https://openalex.org/W3136492254","https://openalex.org/W3137695714","https://openalex.org/W3138819813","https://openalex.org/W4285051865","https://openalex.org/W4297688279","https://openalex.org/W4297779827","https://openalex.org/W6638238755","https://openalex.org/W6639204139","https://openalex.org/W6640425456","https://openalex.org/W6681009388","https://openalex.org/W6683590716","https://openalex.org/W6685133223","https://openalex.org/W6694954494","https://openalex.org/W6713134421","https://openalex.org/W6729956949","https://openalex.org/W6743428213","https://openalex.org/W6745136726","https://openalex.org/W6748579715","https://openalex.org/W6748645487","https://openalex.org/W6754427640","https://openalex.org/W6758857762","https://openalex.org/W6762718338","https://openalex.org/W6762913911","https://openalex.org/W6763310536","https://openalex.org/W6763485134","https://openalex.org/W6767883727","https://openalex.org/W6769209158","https://openalex.org/W6770592442","https://openalex.org/W6771245373","https://openalex.org/W6771497439","https://openalex.org/W6780851395"],"related_works":["https://openalex.org/W11531451","https://openalex.org/W770098","https://openalex.org/W12934963","https://openalex.org/W1266808","https://openalex.org/W12967685","https://openalex.org/W2867368","https://openalex.org/W2655176","https://openalex.org/W4052871","https://openalex.org/W11095331","https://openalex.org/W6169193"],"abstract_inverted_index":{"Data":[0],"augmentations":[1],"are":[2,45,113],"important":[3],"ingredients":[4],"in":[5,14,56,115,127],"the":[6,46,116,123],"recipe":[7],"for":[8],"training":[9],"robust":[10],"neural":[11,22,43,80,100],"networks,":[12],"especially":[13],"computer":[15],"vision.":[16],"A":[17],"fundamental":[18],"question":[19],"is":[20],"whether":[21],"network":[23,81],"features":[24,55,82,103,112],"encode":[25,102],"data":[26,86],"augmentation":[27,50,70,87,106,124],"transformations.":[28,51],"To":[29],"answer":[30],"this":[31],"question,":[32],"we":[33,108],"introduce":[34],"a":[35],"systematic":[36],"approach":[37,53],"to":[38,64,105],"investigate":[39],"which":[40],"layers":[41,118],"of":[42,49,119],"networks":[44,101],"most":[47],"predictive":[48],"Our":[52],"uses":[54],"pre-trained":[57],"vision":[58],"models":[59],"with":[60,94],"minimal":[61],"additional":[62],"processing":[63],"predict":[65,85,91],"common":[66],"properties":[67],"transformed":[68],"by":[69],"(scale,":[71],"aspect":[72],"ratio,":[73],"hue,":[74],"saturation,":[75],"contrast,":[76],"and":[77],"brightness).":[78],"Surprisingly,":[79],"not":[83],"only":[84],"transformations,":[88,107],"but":[89],"they":[90],"many":[92],"transformations":[93],"high":[95],"accuracy.":[96],"After":[97],"validating":[98],"that":[99,110],"corresponding":[104],"show":[109],"these":[111],"encoded":[114],"early":[117],"modern":[120],"CNNs,":[121],"though":[122],"signal":[125],"fades":[126],"deeper":[128],"layers.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}