{"id":"https://openalex.org/W4402595296","doi":"https://doi.org/10.1109/icce-taiwan62264.2024.10674242","title":"ReActXGB: A Hybrid Binary Convolutional Neural Network Architecture for Improved Performance and Computational Efficiency","display_name":"ReActXGB: A Hybrid Binary Convolutional Neural Network Architecture for Improved Performance and Computational Efficiency","publication_year":2024,"publication_date":"2024-07-09","ids":{"openalex":"https://openalex.org/W4402595296","doi":"https://doi.org/10.1109/icce-taiwan62264.2024.10674242"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan62264.2024.10674242","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icce-taiwan62264.2024.10674242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","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/A5113209100","display_name":"Po-Hsun Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Po-Hsun Chu","raw_affiliation_strings":["National Central University,Depart. of Computer Science and Information Engineering,Taoyuan,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Central University,Depart. of Computer Science and Information Engineering,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073238142","display_name":"Ching-Han Chen","orcid":"https://orcid.org/0000-0003-4560-0889"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ching-Han Chen","raw_affiliation_strings":["National Central University,Depart. of Computer Science and Information Engineering,Taoyuan,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Central University,Depart. of Computer Science and Information Engineering,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113209100"],"corresponding_institution_ids":["https://openalex.org/I22265921"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13546137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"327","last_page":"328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.7646999955177307,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.7646999955177307,"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/computer-science","display_name":"Computer science","score":0.7624962329864502},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6418607234954834},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5742824077606201},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5131033658981323},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.49202534556388855},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.32546383142471313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2991766035556793},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.11562585830688477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08505120873451233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7624962329864502},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6418607234954834},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5742824077606201},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5131033658981323},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.49202534556388855},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.32546383142471313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2991766035556793},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.11562585830688477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08505120873451233},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan62264.2024.10674242","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icce-taiwan62264.2024.10674242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.7200000286102295,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2295598076","https://openalex.org/W2300242332","https://openalex.org/W3104151879","https://openalex.org/W3130641740","https://openalex.org/W4386071500"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W4312417841","https://openalex.org/W2038503502"],"abstract_inverted_index":{"Binary":[0],"convolutional":[1,91],"neural":[2,20],"networks":[3,21,109],"(BCNNs)":[4],"provide":[5],"a":[6,25,33,46,71,81,133],"potential":[7],"solution":[8],"to":[9,54,69,100],"reduce":[10],"the":[11,37,55,60,89,102,118],"memory":[12],"requirements":[13],"and":[14,29,63,107,141],"computational":[15,30,48,113],"costs":[16],"associated":[17],"with":[18,95,132],"deep":[19],"(DNNs).":[22],"However,":[23],"achieving":[24],"trade-off":[26],"between":[27,105],"performance":[28,103],"resources":[31],"remains":[32],"significant":[34,47],"challenge.":[35],"Furthermore,":[36],"fully":[38,64,90],"connected":[39,65],"layer":[40,62,66,92],"of":[41,58,93,135],"BCNNs":[42,106],"has":[43],"evolved":[44],"into":[45],"bottleneck.":[49],"This":[50,97],"is":[51],"mainly":[52],"due":[53],"conventional":[56],"practice":[57],"excluding":[59],"input":[61],"from":[67],"binarization":[68],"prevent":[70],"substantial":[72],"loss":[73],"in":[74,128,137,143],"accuracy.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79,87],"propose":[80],"hybrid":[82],"model":[83,144],"named":[84],"ReActXGB,":[85],"where":[86],"replace":[88],"ReActNet-A":[94,125],"XGBoost.":[96],"modification":[98],"targets":[99],"narrow":[101],"gap":[104],"real-valued":[108],"while":[110],"maintaining":[111],"lower":[112],"costs.":[114],"Experimental":[115],"results":[116],"on":[117],"FashionMNIST":[119],"benchmark":[120],"demonstrate":[121],"that":[122],"ReActXGB":[123],"outperforms":[124],"by":[126],"1.47%":[127],"top-1":[129],"accuracy,":[130],"along":[131],"reduction":[134],"7.14%":[136],"floating-point":[138],"operations":[139],"(FLOPs)":[140],"1.02%":[142],"size.":[145]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}