{"id":"https://openalex.org/W3004734842","doi":"https://doi.org/10.1145/3377713.3377721","title":"Binary Convolutional Neural Network with High Accuracy and Compression Rate","display_name":"Binary Convolutional Neural Network with High Accuracy and Compression Rate","publication_year":2019,"publication_date":"2019-12-20","ids":{"openalex":"https://openalex.org/W3004734842","doi":"https://doi.org/10.1145/3377713.3377721","mag":"3004734842"},"language":"en","primary_location":{"id":"doi:10.1145/3377713.3377721","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377713.3377721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence","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/A5041983865","display_name":"Songwei Liu","orcid":"https://orcid.org/0000-0002-9892-0918"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]},{"id":"https://openalex.org/I4210092088","display_name":"Zhejiang Province Institute of Architectural Design and Research","ror":"https://ror.org/00f89ms08","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092088"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Songwei Liu","raw_affiliation_strings":["Institute of VLSI design, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of VLSI design, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4210092088","https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101104281","display_name":"Hongwei Zhu","orcid":"https://orcid.org/0009-0005-8878-4974"},"institutions":[{"id":"https://openalex.org/I4210092088","display_name":"Zhejiang Province Institute of Architectural Design and Research","ror":"https://ror.org/00f89ms08","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092088"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Zhu","raw_affiliation_strings":["Institute of VLSI design, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of VLSI design, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4210092088","https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041983865"],"corresponding_institution_ids":["https://openalex.org/I4210092088","https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.4049,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66961105,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"43","last_page":"48"},"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/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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9973999857902527,"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/computer-science","display_name":"Computer science","score":0.755549430847168},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.7232863903045654},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6800388097763062},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5484859943389893},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.5467795133590698},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5289730429649353},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5055744647979736},{"id":"https://openalex.org/keywords/binary-independence-model","display_name":"Binary Independence Model","score":0.498676061630249},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4430263936519623},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.41807496547698975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41503337025642395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35330379009246826},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.34997087717056274},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.15340930223464966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1466321349143982},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13273891806602478},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.09337940812110901}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.755549430847168},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.7232863903045654},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6800388097763062},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5484859943389893},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.5467795133590698},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5289730429649353},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5055744647979736},{"id":"https://openalex.org/C37061001","wikidata":"https://www.wikidata.org/wiki/Q3531721","display_name":"Binary Independence Model","level":3,"score":0.498676061630249},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4430263936519623},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.41807496547698975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41503337025642395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35330379009246826},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.34997087717056274},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.15340930223464966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1466321349143982},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13273891806602478},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.09337940812110901},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3377713.3377721","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377713.3377721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1902934009","https://openalex.org/W1976948919","https://openalex.org/W2097117768","https://openalex.org/W2107438106","https://openalex.org/W2117539524","https://openalex.org/W2150469677","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2242818861","https://openalex.org/W2271840356","https://openalex.org/W2300242332","https://openalex.org/W2319920447","https://openalex.org/W2335728318","https://openalex.org/W2469490737","https://openalex.org/W2542517113","https://openalex.org/W2559655401","https://openalex.org/W2594481151","https://openalex.org/W2604272474","https://openalex.org/W2604700561","https://openalex.org/W2612690371","https://openalex.org/W2620236356","https://openalex.org/W2753301142","https://openalex.org/W2799243248","https://openalex.org/W2887447938","https://openalex.org/W2913668833","https://openalex.org/W2949117887","https://openalex.org/W2952432176","https://openalex.org/W2964014798","https://openalex.org/W2964078006","https://openalex.org/W2964121744","https://openalex.org/W2964133305","https://openalex.org/W3118608800","https://openalex.org/W6631190155","https://openalex.org/W6685405536"],"related_works":["https://openalex.org/W3093612317","https://openalex.org/W2175746458","https://openalex.org/W2732542196","https://openalex.org/W2760085659","https://openalex.org/W2883200793","https://openalex.org/W2738221750","https://openalex.org/W3012978760","https://openalex.org/W2912288872","https://openalex.org/W2940661641","https://openalex.org/W2758063741"],"abstract_inverted_index":{"In":[0,23,145,172],"this":[1,89],"paper,":[2],"we":[3,91,101,120,180],"propose":[4,121],"an":[5],"efficient":[6,53],"scheme":[7],"to":[8,32,82,122,126,129,133,147,174],"train":[9],"a":[10,159,190],"binary":[11,24,58,109],"convolutional":[12],"neural":[13,25,72],"network":[14],"that":[15,103],"has":[16],"high":[17],"compression":[18,138,178],"rate":[19,139],"and":[20,28,66,154],"classification":[21],"accuracy.":[22],"networks,":[26],"weights":[27],"activations":[29],"are":[30],"binarized":[31],"+1":[33],"or":[34],"-1.":[35],"This":[36],"brings":[37],"two":[38],"benefits:":[39],"1)The":[40],"model":[41],"size":[42],"is":[43,111],"greatly":[44],"reduced;":[45],"2)Arithmetic":[46],"operations":[47,55],"can":[48],"be":[49],"replaced":[50],"by":[51,114],"more":[52,160],"bitwise":[54],"based":[56],"on":[57],"values,":[59],"resulting":[60],"in":[61,76,168],"much":[62],"faster":[63],"inference":[64],"speed":[65],"lower":[67],"power":[68],"consumption.":[69],"However,":[70],"binarizing":[71],"networks":[73,110],"will":[74],"result":[75],"severe":[77],"prediction":[78],"accuracy":[79],"degradation":[80],"compared":[81],"their":[83],"counterpart":[84],"full-precision":[85],"networks.":[86],"To":[87],"solve":[88],"problem,":[90],"apply":[92,123,130],"three":[93],"strategies:":[94],"1)":[95],"By":[96],"summarizing":[97],"the":[98,104,115,142,152,166,177,183,187],"previous":[99],"work,":[100],"conclude":[102],"large":[105],"performance":[106],"loss":[107],"of":[108,117,189],"mainly":[112],"caused":[113],"binarization":[116],"activations,":[118],"so":[119],"multiple":[124,131],"banalizations":[125,132],"activations.":[127],"Compared":[128],"weights,":[134],"it":[135],"effectively":[136],"maintains":[137],"while":[140],"improving":[141],"accuracy;":[143],"2)":[144],"order":[146,173],"alleviate":[148],"gradient":[149],"mismatches":[150],"between":[151],"forward":[153],"backward":[155,169],"propagation,":[156],"We":[157],"adopt":[158],"precise":[161],"differentiable":[162],"approximation":[163],"when":[164],"calculating":[165],"gradients":[167],"propagation;":[170],"3)":[171],"further":[175],"improve":[176],"rate,":[179],"also":[181],"binarize":[182],"last":[184],"layer":[185],"with":[186],"help":[188],"scale":[191],"layer.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
