{"id":"https://openalex.org/W2905527783","doi":"https://doi.org/10.1109/iccais.2018.8570503","title":"Parasitic Network: Learning-Based Network Downsizing of Very Deep Neural Networks for Computer Vision","display_name":"Parasitic Network: Learning-Based Network Downsizing of Very Deep Neural Networks for Computer Vision","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2905527783","doi":"https://doi.org/10.1109/iccais.2018.8570503","mag":"2905527783"},"language":"en","primary_location":{"id":"doi:10.1109/iccais.2018.8570503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2018.8570503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Parasitic_Network_Learning-Based_Network_Downsizing_of_Very_Deep_Neural_Networks_for_Computer_Vision/27587880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101783265","display_name":"Jongmin Yu","orcid":"https://orcid.org/0000-0002-0718-9948"},"institutions":[{"id":"https://openalex.org/I205640436","display_name":"Curtin University","ror":"https://ror.org/02n415q13","country_code":"AU","type":"education","lineage":["https://openalex.org/I205640436"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jongmin Yu","raw_affiliation_strings":["Curtin University, Perth, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Curtin University, Perth, Australia","institution_ids":["https://openalex.org/I205640436"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085224820","display_name":"Duyoung Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Duyoung Kim","raw_affiliation_strings":["RMIT Univserity, Melbourne, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT Univserity, Melbourne, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056743652","display_name":"Moongu Jeon","orcid":"https://orcid.org/0000-0002-2775-7789"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moongu Jeon","raw_affiliation_strings":["Gwangju Institute of Science and Technology, Gwangju, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"378","last_page":"383"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9954000115394592,"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/host","display_name":"Host (biology)","score":0.8084546327590942},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7935737371444702},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5924080014228821},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.5883201360702515},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5198724269866943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4923146963119507},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4170071482658386}],"concepts":[{"id":"https://openalex.org/C126831891","wikidata":"https://www.wikidata.org/wiki/Q221673","display_name":"Host (biology)","level":2,"score":0.8084546327590942},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7935737371444702},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5924080014228821},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.5883201360702515},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5198724269866943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4923146963119507},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4170071482658386},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccais.2018.8570503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2018.8570503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.61RMIT_INST:11273352120001341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ICCAIS.2018.8570503","pdf_url":null,"source":{"id":"https://openalex.org/S4306402074","display_name":"RMIT Research Repository (RMIT University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I82951845","host_organization_name":"RMIT University","host_organization_lineage":["https://openalex.org/I82951845"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:figshare.com:article/27587880","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Parasitic_Network_Learning-Based_Network_Downsizing_of_Very_Deep_Neural_Networks_for_Computer_Vision/27587880","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference contribution"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/27587880","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Parasitic_Network_Learning-Based_Network_Downsizing_of_Very_Deep_Neural_Networks_for_Computer_Vision/27587880","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference contribution"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W80079294","https://openalex.org/W1522301498","https://openalex.org/W1575599472","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1885185971","https://openalex.org/W2068730032","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2114766824","https://openalex.org/W2119144962","https://openalex.org/W2120972216","https://openalex.org/W2125389748","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2785745756","https://openalex.org/W2962793481","https://openalex.org/W2963037989","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W2964299589","https://openalex.org/W3008725350","https://openalex.org/W3106250896","https://openalex.org/W6677103964","https://openalex.org/W6678000929","https://openalex.org/W6678583879","https://openalex.org/W6684191040","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2117112636","https://openalex.org/W2001981265","https://openalex.org/W2014134454","https://openalex.org/W3165388193","https://openalex.org/W2371177456","https://openalex.org/W274046748","https://openalex.org/W1804953925","https://openalex.org/W2111375262","https://openalex.org/W4246303233","https://openalex.org/W3139395509"],"abstract_inverted_index":{"In":[0,46],"recent":[1],"research":[2],"on":[3,38,106],"deep":[4],"neural":[5],"network":[6,8,53,57,75,80,102,121,152],"(DNN),":[7],"downsizing":[9,21,122],"is":[10,76,103,158],"one":[11],"of":[12,24,36,72,116],"practical":[13],"issues":[14],"for":[15,34],"computational":[16],"and":[17,66,126,136],"memory":[18],"efficiency.":[19],"Specifically,":[20],"or":[22,43],"compression":[23],"networks":[25],"minimizing":[26],"the":[27,55,61,73,89,100,110,120,134],"performance":[28,148],"degradation":[29],"becomes":[30],"a":[31,51,64,92],"critical":[32],"problem":[33],"deployment":[35],"DNNs":[37],"resource-limited":[39],"environments":[40],"such":[41],"mobile":[42],"embedded":[44],"platforms.":[45],"this":[47],"paper,":[48],"we":[49],"propose":[50],"compressed":[52],"called":[54],"parasitic":[56,74],"(PN)":[58],"inspired":[59],"by":[60,133],"relationship":[62],"between":[63],"parasite":[65],"host":[67,79,101,111,151],"in":[68,85,123],"nature.":[69],"The":[70,78,94,139],"concept":[71],"straightforward.":[77],"provides":[81],"their":[82,150,155],"mapping":[83],"results":[84,141],"each":[86],"layer":[87],"to":[88,119,149],"PN":[90,95,144],"as":[91],"feed.":[93],"that":[96,143],"much":[97,159],"shallower":[98],"than":[99],"trained":[104],"based":[105],"given":[107],"information":[108],"from":[109],"network.":[112],"We":[113],"demonstrate":[114],"efficiency":[115],"our":[117],"approach":[118],"image":[124],"classification":[125],"object":[127],"detection":[128],"problems":[129],"which":[130],"have":[131],"conquered":[132],"deeper":[135],"bigger":[137],"networks.":[138],"experimental":[140],"show":[142],"can":[145],"provide":[146],"sample":[147],"even":[153],"though":[154],"architectural":[156],"scale":[157],"smaller.":[160]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}