{"id":"https://openalex.org/W4214870202","doi":"https://doi.org/10.1109/icaiic54071.2022.9722632","title":"Effect of the Period of the Fourier Series Approximation for Binarized Neural Network","display_name":"Effect of the Period of the Fourier Series Approximation for Binarized Neural Network","publication_year":2022,"publication_date":"2022-02-21","ids":{"openalex":"https://openalex.org/W4214870202","doi":"https://doi.org/10.1109/icaiic54071.2022.9722632"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic54071.2022.9722632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic54071.2022.9722632","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5023922193","display_name":"SeonYong Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"SeonYong Lee","raw_affiliation_strings":["INMC, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INMC, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I139264467","https://openalex.org/I2802457231"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083191065","display_name":"Hee-Youl Kwak","orcid":"https://orcid.org/0000-0002-4381-1968"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"Hee-Youl Kwak","raw_affiliation_strings":["INMC, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INMC, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I139264467","https://openalex.org/I2802457231"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000078617","display_name":"Jong\u2010Seon No","orcid":"https://orcid.org/0000-0002-3946-0958"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"Jong-Seon No","raw_affiliation_strings":["INMC, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INMC, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I139264467","https://openalex.org/I2802457231"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2774,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57731278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"262","last_page":"265"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9983000159263611,"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/T12676","display_name":"Machine Learning and ELM","score":0.9905999898910522,"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/fourier-series","display_name":"Fourier series","score":0.730672299861908},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7001166939735413},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6353123784065247},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.6287945508956909},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.585554838180542},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5620318651199341},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.5171182155609131},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5075696706771851},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4965437054634094},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4929208755493164},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4804815351963043},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4787161350250244},{"id":"https://openalex.org/keywords/function-approximation","display_name":"Function approximation","score":0.46717506647109985},{"id":"https://openalex.org/keywords/discrete-fourier-series","display_name":"Discrete Fourier series","score":0.4402107298374176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4187540113925934},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41496992111206055},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.3281935453414917},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.18098753690719604},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1443316638469696},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10373848676681519}],"concepts":[{"id":"https://openalex.org/C207864730","wikidata":"https://www.wikidata.org/wiki/Q179467","display_name":"Fourier series","level":2,"score":0.730672299861908},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7001166939735413},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6353123784065247},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6287945508956909},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.585554838180542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5620318651199341},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.5171182155609131},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5075696706771851},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4965437054634094},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4929208755493164},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4804815351963043},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4787161350250244},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.46717506647109985},{"id":"https://openalex.org/C175225751","wikidata":"https://www.wikidata.org/wiki/Q15927242","display_name":"Discrete Fourier series","level":5,"score":0.4402107298374176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4187540113925934},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41496992111206055},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.3281935453414917},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.18098753690719604},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1443316638469696},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10373848676681519},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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":1,"locations":[{"id":"doi:10.1109/icaiic54071.2022.9722632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic54071.2022.9722632","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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":18,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2163605009","https://openalex.org/W2242818861","https://openalex.org/W2300242332","https://openalex.org/W2963163009","https://openalex.org/W2968917279","https://openalex.org/W3004061291","https://openalex.org/W3213568228","https://openalex.org/W4295262505","https://openalex.org/W4301188113","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6684191040","https://openalex.org/W6690026940","https://openalex.org/W6693397755","https://openalex.org/W6767164110","https://openalex.org/W6776469097","https://openalex.org/W6791636759"],"related_works":["https://openalex.org/W2094684004","https://openalex.org/W2099309112","https://openalex.org/W1574935133","https://openalex.org/W4298260447","https://openalex.org/W4387646299","https://openalex.org/W3022846395","https://openalex.org/W2370547058","https://openalex.org/W6842695","https://openalex.org/W2751880894","https://openalex.org/W2017823752"],"abstract_inverted_index":{"The":[0,159],"construction":[1,23],"of":[2,19,61,88,104,110,112,131,142,148,155,170],"low":[3],"complexity":[4],"models":[5],"for":[6,25,134],"the":[7,20,38,56,59,64,68,86,89,93,102,105,108,113,118,122,129,132,135,139,143,146,149,153,156,162,171,175],"neural":[8,28,43],"networks":[9,44],"is":[10,31,48,67,83],"an":[11],"important":[12],"issue":[13],"in":[14,58],"practical,":[15],"real-world":[16],"scenarios.":[17],"One":[18,77],"most":[21],"famous":[22],"methods":[24],"a":[26,125,167],"simple":[27],"network":[29,119],"model":[30],"to":[32,54,79,84],"represent":[33,55],"weights":[34],"and":[35,107,138],"activations":[36],"by":[37,92],"1-bit":[39],"quantization,":[40],"called":[41],"binarized":[42],"(BNNs).":[45],"However,":[46],"it":[47],"still":[49],"under":[50],"research":[51],"on":[52,117,161],"how":[53],"gradient":[57,87,144],"backpropagation":[60],"BNNs":[62,177],"because":[63],"activation":[65],"function":[66,70,91,137],"sign":[69,90,136],"whose":[71],"gradients":[72],"are":[73],"zero":[74],"almost":[75],"everywhere.":[76],"way":[78],"address":[80],"this":[81,98],"problem":[82],"approximate":[85],"Fourier":[94,114],"series":[95,115],"representation.":[96],"In":[97],"paper,":[99],"we":[100],"analyze":[101],"effect":[103],"period":[106,123,150,172],"number":[109],"terms":[111],"representation":[116],"accuracy.":[120],"Since":[121],"has":[124],"direct":[126],"relationship":[127],"with":[128,178],"degree":[130],"approximation":[133],"oscillation":[140],"behavior":[141],"function,":[145],"choice":[147,169],"significantly":[151],"affects":[152],"accuracy":[154],"BNN":[157],"model.":[158],"experiments":[160],"CIFAR-10":[163],"dataset":[164],"demonstrate":[165],"that":[166],"proper":[168],"can":[173],"outperform":[174],"conventional":[176],"straight":[179],"through":[180],"estimator.":[181]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
