{"id":"https://openalex.org/W3090753555","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207372","title":"BIBNet: An Efficient Super Resolution with Bottleneck-In-Bottleneck","display_name":"BIBNet: An Efficient Super Resolution with Bottleneck-In-Bottleneck","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090753555","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207372","mag":"3090753555"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5112998078","display_name":"Simyung Chang","orcid":"https://orcid.org/0000-0001-7750-191X"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Simyung Chang","raw_affiliation_strings":["Visual Display Division, Samsung Electronics, Suwon, Korea"],"affiliations":[{"raw_affiliation_string":"Visual Display Division, Samsung Electronics, Suwon, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035593280","display_name":"Keuntek Lee","orcid":"https://orcid.org/0000-0003-4901-7842"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Keuntek Lee","raw_affiliation_strings":["Visual Display Division, Samsung Electronics, Suwon, Korea"],"affiliations":[{"raw_affiliation_string":"Visual Display Division, Samsung Electronics, Suwon, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113918590","display_name":"S. C. Jain","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Shobhit Jain","raw_affiliation_strings":["Visual Display Division, Samsung Electronics, Suwon, Korea"],"affiliations":[{"raw_affiliation_string":"Visual Display Division, Samsung Electronics, Suwon, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023817948","display_name":"Cheul-Hee Hahm","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Cheul-hee Hahm","raw_affiliation_strings":["Visual Display Division, Samsung Electronics, Suwon, Korea"],"affiliations":[{"raw_affiliation_string":"Visual Display Division, Samsung Electronics, Suwon, Korea","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112998078"],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":null,"apc_paid":null,"fwci":0.0977,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40602944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9980000257492065,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9972000122070312,"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/bottleneck","display_name":"Bottleneck","score":0.9701827764511108},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7866178750991821},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6808410882949829},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6287115216255188},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5438658595085144},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.47881561517715454},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.43598899245262146},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.428516685962677},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42507049441337585},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.42201003432273865},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4154372215270996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3682650327682495},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30260398983955383},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.1305140256881714},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08007115125656128}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.9701827764511108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7866178750991821},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6808410882949829},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6287115216255188},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5438658595085144},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.47881561517715454},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.43598899245262146},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.428516685962677},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42507049441337585},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.42201003432273865},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4154372215270996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3682650327682495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30260398983955383},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.1305140256881714},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08007115125656128},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W935139217","https://openalex.org/W1522301498","https://openalex.org/W1791560514","https://openalex.org/W1885185971","https://openalex.org/W1919542679","https://openalex.org/W1930824406","https://openalex.org/W1950594372","https://openalex.org/W2047920195","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2121927366","https://openalex.org/W2150081556","https://openalex.org/W2200594420","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2507235960","https://openalex.org/W2520322935","https://openalex.org/W2607041014","https://openalex.org/W2612445135","https://openalex.org/W2740139074","https://openalex.org/W2741137940","https://openalex.org/W2747898905","https://openalex.org/W2752387826","https://openalex.org/W2866634454","https://openalex.org/W2908108015","https://openalex.org/W2913541967","https://openalex.org/W2952670936","https://openalex.org/W2962971773","https://openalex.org/W2963097630","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963182372","https://openalex.org/W2963372104","https://openalex.org/W2963645458","https://openalex.org/W2963729050","https://openalex.org/W2964081807","https://openalex.org/W2964121744","https://openalex.org/W2964125708","https://openalex.org/W3129158555","https://openalex.org/W4297775537","https://openalex.org/W4377561911","https://openalex.org/W6624640001","https://openalex.org/W6631190155","https://openalex.org/W6638194035","https://openalex.org/W6690498163","https://openalex.org/W6724673846","https://openalex.org/W6725327932","https://openalex.org/W6737664043","https://openalex.org/W6740474667","https://openalex.org/W6744992241","https://openalex.org/W6753074096","https://openalex.org/W6758222532","https://openalex.org/W6759278257"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W4301867275","https://openalex.org/W2790610275"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"have":[3],"enabled":[4],"remarkable":[5],"progress":[6],"in":[7,34,63,78,91],"the":[8,42,64,88,92],"field":[9],"of":[10,52,87,94,104,129],"single":[11],"image":[12],"super":[13],"resolution":[14],"(SR).":[15],"However,":[16],"these":[17],"models":[18,46],"are":[19],"often":[20],"large":[21,105],"and":[22,36,71,122,131,141],"complex":[23,156],"to":[24,125,149],"be":[25,50],"applied":[26],"for":[27],"real-world":[28],"applications":[29],"with":[30,58,112,138,154],"limited":[31],"resources":[32],"as":[33,47],"mobile":[35],"embedded":[37],"systems.":[38],"We":[39,108],"investigate":[40],"whether":[41],"typical":[43],"low":[44],"latency":[45],"MobileNet":[48],"can":[49,117],"expected":[51],"comparable":[53],"efficiency":[54],"at":[55],"SR":[56,61,152],"tasks":[57],"recently":[59],"reported":[60],"performance":[62,147],"literature.":[65],"To":[66],"this":[67,79],"end,":[68],"a":[69,95,127],"moderate":[70],"effective":[72],"architecture,":[73],"Bottleneck-In-Bottleneck":[74],"(BIB),":[75],"is":[76],"introduced":[77],"paper.":[80],"The":[81],"BIB":[82,114],"uses":[83],"multiple":[84,113],"expansion":[85],"factors":[86,103],"residual":[89],"blocks":[90],"form":[93],"bottleneck,":[96],"reducing":[97],"computation":[98],"complexity":[99],"while":[100],"utilizing":[101],"advantageous":[102],"feature":[106],"dimensions.":[107],"also":[109],"propose":[110],"BIBNet":[111,143],"blocks,":[115],"which":[116],"easily":[118],"adjust":[119],"its":[120],"size":[121],"computational":[123],"cost":[124],"create":[126],"variety":[128],"efficient":[130],"high-performance":[132],"models.":[133],"Extensive":[134],"experiments":[135],"show":[136],"that,":[137],"fewer":[139],"parameters":[140],"computations,":[142],"achieves":[144],"highly":[145],"competitive":[146],"compared":[148],"other":[150],"conventional":[151],"methods":[153],"more":[155],"architectures.":[157]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}