{"id":"https://openalex.org/W4313318667","doi":"https://doi.org/10.1109/tmm.2022.3233255","title":"Cellular Binary Neural Network for Accurate Image Classification and Semantic Segmentation","display_name":"Cellular Binary Neural Network for Accurate Image Classification and Semantic Segmentation","publication_year":2022,"publication_date":"2022-12-30","ids":{"openalex":"https://openalex.org/W4313318667","doi":"https://doi.org/10.1109/tmm.2022.3233255"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2022.3233255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3233255","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5010601964","display_name":"Xichuan Zhou","orcid":"https://orcid.org/0000-0002-3304-3045"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xichuan Zhou","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-3304-3045","affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007211058","display_name":"Rui Ding","orcid":"https://orcid.org/0000-0002-8174-1438"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Ding","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721978","display_name":"Yuxiao Wang","orcid":"https://orcid.org/0009-0001-7359-5231"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiao Wang","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102679144","display_name":"Wenjia Wei","orcid":"https://orcid.org/0000-0002-8336-7224"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjia Wei","raw_affiliation_strings":["Huawei Technologies Co. Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018914021","display_name":"Haijun Liu","orcid":"https://orcid.org/0000-0001-5782-4543"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haijun Liu","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-5782-4543","affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1098,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82055152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"25","issue":null,"first_page":"8064","last_page":"8075"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9976000189781189,"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/T12676","display_name":"Machine Learning and ELM","score":0.9976000189781189,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9912999868392944,"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/T10320","display_name":"Neural Networks and Applications","score":0.9749000072479248,"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":0.793708860874176},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6954655051231384},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6876246333122253},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6602113246917725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6127897500991821},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5858364701271057},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.577254056930542},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5166547894477844},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4954136610031128},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4807050824165344},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4665961265563965},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46515092253685},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4471495449542999},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4289305806159973},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28075292706489563},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10625654458999634},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09497177600860596}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.793708860874176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6954655051231384},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6876246333122253},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6602113246917725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6127897500991821},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5858364701271057},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.577254056930542},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5166547894477844},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4954136610031128},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4807050824165344},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4665961265563965},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46515092253685},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4471495449542999},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4289305806159973},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28075292706489563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10625654458999634},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09497177600860596},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2022.3233255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3233255","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1701467326","display_name":null,"funder_award_id":"U2133211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4202674976","display_name":null,"funder_award_id":"2020M673135","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8673984432","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u56fe\u50cf\u5f31\u76d1\u7763\u6df1\u5ea6\u5b66\u4e60\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8842490266","display_name":null,"funder_award_id":"62001063","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2108598243","https://openalex.org/W2144794286","https://openalex.org/W2194775991","https://openalex.org/W2242818861","https://openalex.org/W2300242332","https://openalex.org/W2469490737","https://openalex.org/W2565639579","https://openalex.org/W2586654419","https://openalex.org/W2630837129","https://openalex.org/W2742400085","https://openalex.org/W2884150179","https://openalex.org/W2887447938","https://openalex.org/W2898466789","https://openalex.org/W2942140333","https://openalex.org/W2954048742","https://openalex.org/W2957777252","https://openalex.org/W2962298324","https://openalex.org/W2963480671","https://openalex.org/W2964133305","https://openalex.org/W2964195914","https://openalex.org/W2970691381","https://openalex.org/W2976833605","https://openalex.org/W2982344224","https://openalex.org/W2982605490","https://openalex.org/W3000556572","https://openalex.org/W3004061291","https://openalex.org/W3008515144","https://openalex.org/W3020701269","https://openalex.org/W3034297393","https://openalex.org/W3035219584","https://openalex.org/W3095248970","https://openalex.org/W3097297321","https://openalex.org/W3104151879","https://openalex.org/W3108720720","https://openalex.org/W3118608800","https://openalex.org/W3121626821","https://openalex.org/W3173202379","https://openalex.org/W3175426148","https://openalex.org/W3176278386","https://openalex.org/W3176946833","https://openalex.org/W4205709366","https://openalex.org/W4206211125","https://openalex.org/W4214888034","https://openalex.org/W6638523607","https://openalex.org/W6638783484","https://openalex.org/W6677580257","https://openalex.org/W6684563725","https://openalex.org/W6690026940","https://openalex.org/W6693397755","https://openalex.org/W6720242923","https://openalex.org/W6729788942","https://openalex.org/W6730047919","https://openalex.org/W6739696289","https://openalex.org/W6744700018","https://openalex.org/W6762718338","https://openalex.org/W6763503671","https://openalex.org/W6766978945","https://openalex.org/W6768409960","https://openalex.org/W6772326514","https://openalex.org/W6772803787","https://openalex.org/W6779662352","https://openalex.org/W6783467810","https://openalex.org/W6784469588","https://openalex.org/W6787972765","https://openalex.org/W6791636759","https://openalex.org/W6795891359"],"related_works":["https://openalex.org/W1663079876","https://openalex.org/W2069133146","https://openalex.org/W2017545316","https://openalex.org/W2100576949","https://openalex.org/W2159686533","https://openalex.org/W4242339654","https://openalex.org/W2910954186","https://openalex.org/W4205999209","https://openalex.org/W4288570796","https://openalex.org/W2444525338"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"the":[3,23,32,73,79,86,99,115,118,124,134,139,148,152,165,169,173,182],"Cellular":[4],"Binary":[5],"Neural":[6],"Network":[7],"(CBNN),":[8],"which":[9,37,144],"is":[10],"an":[11],"efficient":[12],"deep":[13],"neural":[14,105],"network":[15],"with":[16,56],"binary":[17,104,120],"weights":[18],"and":[19,54,66,78,88,180],"activations.":[20],"To":[21],"address":[22],"challenge":[24],"of":[25,109,117,133],"performance":[26,175],"drop":[27],"caused":[28],"by":[29,72,93,147],"low-precision":[30],"representation,":[31],"CBNN":[33,100,125,130],"adopts":[34],"multiple":[35,135],"subnets":[36,136],"are":[38,49,69,145],"connected":[39],"via":[40],"learnable":[41],"global":[42],"lateral":[43,47,64,97],"paths.":[44],"The":[45,62],"introduced":[46],"connections":[48,65],"assumed":[50],"to":[51,58,113,137],"be":[52],"sparse":[53,81],"grouped":[55],"respect":[57],"different":[59],"source":[60],"layers.":[61],"inter-network":[63],"inner-network":[67],"parameters":[68],"simultaneously":[70],"optimized":[71,95],"distributional":[74],"loss,":[75],"classification":[76,110],"loss":[77],"group":[80],"regularization":[82],"term.":[83],"Experiments":[84,156],"on":[85,126,157],"CIFAR-10":[87],"ImageNet":[89],"datasets":[90],"showed":[91],"that,":[92,163],"incorporating":[94],"group-sparse":[96],"paths,":[98],"outperformed":[101],"many":[102],"state-of-the-art":[103],"networks":[106,179],"in":[107,151],"terms":[108],"accuracy.":[111],"Besides,":[112],"verify":[114],"generalization":[116],"proposed":[119,170],"model,":[121],"we":[122],"extended":[123],"semantic":[127],"segmentation":[128,160,167],"task.":[129],"takes":[131],"advantage":[132],"derive":[138],"more":[140],"informative":[141],"feature":[142],"maps":[143],"computed":[146],"parallel":[149],"aggregation":[150],"last":[153],"convolution":[154],"block.":[155],"PASCAL":[158],"VOC":[159],"dataset":[161],"demonstrated":[162],"under":[164],"same":[166],"settings,":[168],"method":[171],"achieved":[172],"superior":[174],"over":[176],"other":[177],"compared":[178],"even":[181],"full-precision":[183],"counterpart.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}