{"id":"https://openalex.org/W4224443337","doi":"https://doi.org/10.1155/2022/4437446","title":"A Deep Neural Network Based on Circular Representation for Target Detection","display_name":"A Deep Neural Network Based on Circular Representation for Target Detection","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224443337","doi":"https://doi.org/10.1155/2022/4437446"},"language":"en","primary_location":{"id":"doi:10.1155/2022/4437446","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/4437446","pdf_url":"https://downloads.hindawi.com/journals/js/2022/4437446.pdf","source":{"id":"https://openalex.org/S96783963","display_name":"Journal of Sensors","issn_l":"1687-725X","issn":["1687-725X","1687-7268"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/js/2022/4437446.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035508811","display_name":"Cong Lin","orcid":"https://orcid.org/0000-0002-1567-1398"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Lin","raw_affiliation_strings":["College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028493698","display_name":"Zhoujian Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhoujian Chen","raw_affiliation_strings":["College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088718005","display_name":"Yiquan Huang","orcid":"https://orcid.org/0000-0003-3682-7264"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiquan Huang","raw_affiliation_strings":["College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080958374","display_name":"Haoyu Jiang","orcid":"https://orcid.org/0000-0003-3225-6214"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Jiang","raw_affiliation_strings":["College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang /524025, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100629112","display_name":"Wencai Du","orcid":"https://orcid.org/0000-0003-0428-0057"},"institutions":[{"id":"https://openalex.org/I4210108537","display_name":"University of Saint Joseph","ror":"https://ror.org/01m6ap410","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210108537"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wencai Du","raw_affiliation_strings":["Institute of Data Engineering and Sciences, University of Saint Joseph, Macao, China"],"raw_orcid":"https://orcid.org/0000-0003-0428-0057","affiliations":[{"raw_affiliation_string":"Institute of Data Engineering and Sciences, University of Saint Joseph, Macao, China","institution_ids":["https://openalex.org/I4210108537"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100336677","display_name":"Qiong Chen","orcid":"https://orcid.org/0000-0002-3480-7641"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiong Chen","raw_affiliation_strings":["Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing /100084, China"],"raw_orcid":"https://orcid.org/0000-0002-3480-7641","affiliations":[{"raw_affiliation_string":"Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing /100084, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100336677","https://openalex.org/A5100629112"],"corresponding_institution_ids":["https://openalex.org/I4210108537","https://openalex.org/I99065089"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":0.0979,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.33089451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"2022","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9818000197410583,"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/object-detection","display_name":"Object detection","score":0.7149902582168579},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.652574896812439},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6482030153274536},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6405792236328125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5915927886962891},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5787081718444824},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5430883169174194},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.526513934135437},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5092235803604126},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4596770107746124},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4298710823059082},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.4205617308616638},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4190230667591095},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3355700373649597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2163902223110199}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7149902582168579},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.652574896812439},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6482030153274536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6405792236328125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5915927886962891},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5787081718444824},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5430883169174194},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.526513934135437},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5092235803604126},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4596770107746124},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4298710823059082},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.4205617308616638},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4190230667591095},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3355700373649597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2163902223110199},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1155/2022/4437446","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/4437446","pdf_url":"https://downloads.hindawi.com/journals/js/2022/4437446.pdf","source":{"id":"https://openalex.org/S96783963","display_name":"Journal of Sensors","issn_l":"1687-725X","issn":["1687-725X","1687-7268"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sensors","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1155/2022/4437446","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/4437446","pdf_url":"https://downloads.hindawi.com/journals/js/2022/4437446.pdf","source":{"id":"https://openalex.org/S96783963","display_name":"Journal of Sensors","issn_l":"1687-725X","issn":["1687-725X","1687-7268"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1055662248","display_name":null,"funder_award_id":"2021A1515011847","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2370966706","display_name":null,"funder_award_id":"62072121","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G5501497924","display_name":null,"funder_award_id":"62072121","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G585186276","display_name":null,"funder_award_id":"2021A1515011847","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224443337.pdf","grobid_xml":"https://content.openalex.org/works/W4224443337.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1483870316","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1973759501","https://openalex.org/W1974295693","https://openalex.org/W2022637272","https://openalex.org/W2060230922","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2133382819","https://openalex.org/W2163605009","https://openalex.org/W2164468282","https://openalex.org/W2167790077","https://openalex.org/W2194775991","https://openalex.org/W2307770531","https://openalex.org/W2570343428","https://openalex.org/W2613718673","https://openalex.org/W2622826443","https://openalex.org/W2884561390","https://openalex.org/W2910121883","https://openalex.org/W2963037989","https://openalex.org/W2972006294","https://openalex.org/W2991833700","https://openalex.org/W3000322757","https://openalex.org/W3001083904","https://openalex.org/W3033807052","https://openalex.org/W3035396860","https://openalex.org/W3039368862","https://openalex.org/W3100321043","https://openalex.org/W3105054740","https://openalex.org/W3106250896","https://openalex.org/W3132455321","https://openalex.org/W3167976421","https://openalex.org/W3175388214","https://openalex.org/W4206029786","https://openalex.org/W4293584584","https://openalex.org/W6687483927","https://openalex.org/W6750227808","https://openalex.org/W6760424586","https://openalex.org/W6772750526","https://openalex.org/W6788611029"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3103566983","https://openalex.org/W2949096641","https://openalex.org/W2969228573","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W2963690996"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"network":[2,69,109,132],"(CNN)":[3],"model":[4,211],"based":[5,37],"on":[6,38,61,180],"deep":[7],"learning":[8],"has":[9],"excellent":[10],"performance":[11],"for":[12,136],"target":[13],"detection.":[14],"However,":[15],"the":[16,22,31,39,50,54,62,68,94,105,108,113,117,128,131,137,148,157,167,170,235,242],"detection":[17,34,81,203,231,248],"effect":[18],"is":[19,24,153,225],"poor":[20],"when":[21],"object":[23,33,80,230],"circular":[25,55,79,85,100,144],"or":[26],"tubular":[27,86,145,251],"because":[28],"most":[29],"of":[30,64,107,116,119,130,151,169,205,214,222,237,249],"existing":[32],"methods":[35],"are":[36],"traditional":[40,95],"rectangular":[41,96],"box":[42,97],"to":[43,126,155,173,191,207,227],"detect":[44,125],"and":[45,58,66,76,112,183,209,233],"recognize":[46],"objects.":[47,146],"To":[48],"solve":[49],"problem,":[51],"we":[52,103],"propose":[53],"representation":[56],"structure":[57],"RepVGG":[59,152],"module":[60,172],"basis":[63],"CenterNet":[65],"expand":[67],"prediction":[70,133],"structure,":[71,134],"thus":[72],"proposing":[73],"a":[74,99,123,187,202,210,219],"high-precision":[75],"high-efficiency":[77],"lightweight":[78],"method":[82,190],"RebarDet.":[83,193],"Specifically,":[84],"type":[87],"objects":[88,120,252],"will":[89],"be":[90],"optimized":[91,135],"by":[92,161],"replacing":[93],"with":[98],"box.":[101],"Second,":[102],"improve":[104],"resolution":[106],"feature":[110,158],"map":[111],"upper":[114],"limit":[115],"number":[118],"detected":[121],"in":[122,143],"single":[124],"achieve":[127,201],"expansion":[129],"dense":[138],"phenomenon":[139],"that":[140,198],"often":[141],"occurs":[142],"Finally,":[147],"multibranch":[149],"topology":[150],"introduced":[154],"sum":[156],"information":[159],"extracted":[160],"different":[162],"convolution":[163,171],"modules,":[164],"which":[165,224],"improves":[166],"ability":[168],"extract":[174],"information.":[175],"We":[176],"conducted":[177],"extensive":[178],"experiments":[179],"rebar":[181],"datasets":[182],"used":[184],"AB-Score":[185],"as":[186],"new":[188],"evaluation":[189],"evaluate":[192],"The":[194],"experimental":[195],"results":[196],"show":[197],"RebarDet":[199],"can":[200],"accuracy":[204],"up":[206],"0.8114":[208],"inference":[212],"speed":[213],"6.9":[215],"fps":[216],"while":[217],"maintaining":[218],"moderate":[220],"amount":[221],"parameters,":[223],"superior":[226],"other":[228],"mainstream":[229],"models":[232],"verifies":[234],"effectiveness":[236],"our":[238],"proposed":[239],"method.":[240],"At":[241],"same":[243],"time,":[244],"RebarDet\u2019s":[245],"high":[246],"precision":[247],"round":[250],"facilitates":[253],"enterprise":[254],"intelligent":[255],"manufacturing":[256],"processes.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
