{"id":"https://openalex.org/W4385903873","doi":"https://doi.org/10.1142/s0218001423550145","title":"LHFNet: A Fast and Accurate Object Detector Based on CenterNet","display_name":"LHFNet: A Fast and Accurate Object Detector Based on CenterNet","publication_year":2023,"publication_date":"2023-08-18","ids":{"openalex":"https://openalex.org/W4385903873","doi":"https://doi.org/10.1142/s0218001423550145"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001423550145","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001423550145","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5047081251","display_name":"Xianrang Shi","orcid":"https://orcid.org/0000-0002-3440-4033"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianrang Shi","raw_affiliation_strings":["College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-3440-4033","affiliations":[{"raw_affiliation_string":"College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101234887","display_name":"Yang Su","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Su","raw_affiliation_strings":["College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021250639","display_name":"Yan Ti","orcid":"https://orcid.org/0000-0003-0029-8049"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Ti","raw_affiliation_strings":["College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, P. R. China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110718007","display_name":"Tinglun Song","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131005","display_name":"Chery Automobile (China)","ror":"https://ror.org/02xab7z06","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210131005"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tinglun Song","raw_affiliation_strings":["Chery Automobile CO., Ltd, Wuhu, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chery Automobile CO., Ltd, Wuhu, P. R. China","institution_ids":["https://openalex.org/I4210131005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1064,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.37390473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"37","issue":"12","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9919999837875366,"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":0.9900000095367432,"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":0.8328992128372192},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6283782124519348},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6254411935806274},{"id":"https://openalex.org/keywords/hourglass","display_name":"Hourglass","score":0.6203548312187195},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6038439869880676},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5516322255134583},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5274519920349121},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.49967384338378906},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4990718364715576},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.47430920600891113},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46970269083976746},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43316757678985596},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16187450289726257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8328992128372192},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6283782124519348},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6254411935806274},{"id":"https://openalex.org/C127532173","wikidata":"https://www.wikidata.org/wiki/Q179904","display_name":"Hourglass","level":2,"score":0.6203548312187195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6038439869880676},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5516322255134583},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5274519920349121},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.49967384338378906},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4990718364715576},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.47430920600891113},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46970269083976746},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43316757678985596},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16187450289726257},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001423550145","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001423550145","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2008001194","https://openalex.org/W2059645356","https://openalex.org/W3141841835","https://openalex.org/W2380057626","https://openalex.org/W2033695776","https://openalex.org/W2354533751","https://openalex.org/W2755014831","https://openalex.org/W1509096452","https://openalex.org/W2512390310","https://openalex.org/W2079475205"],"abstract_inverted_index":{"This":[0],"paper":[1,23],"proposes":[2],"LHFNet,":[3],"an":[4,50,78],"improved":[5],"object":[6,150],"detection":[7,46,151],"method":[8,131],"based":[9],"on":[10,132],"CenterNet,":[11,42],"which":[12,64,147],"achieves":[13],"a":[14,29,96,138,142],"better":[15],"speed-accuracy":[16],"trade-off.":[17],"The":[18],"main":[19],"contributions":[20],"of":[21,37,41,62,98,126,155],"this":[22,109],"are":[24],"as":[25],"follows:":[26],"We":[27,48,76,92,128],"design":[28,93],"lightweight":[30],"Hourglass":[31],"network":[32,74],"to":[33,56,81,86,101],"reduce":[34],"the":[35,45,58,67,73,82,88,106,114,119,124,133],"number":[36],"parameters":[38],"and":[39,94,118,136,158],"computations":[40],"thus":[43],"improving":[44],"speed.":[47],"introduce":[49],"intermediate":[51],"feature":[52,59,90,115],"map":[53,85,116],"fusion":[54,117],"module":[55,80,121],"enhance":[57],"extraction":[60],"capability":[61],"Hourglass,":[63],"compensates":[65],"for":[66],"possible":[68],"performance":[69,125],"degradation":[70],"caused":[71],"by":[72],"simplification.":[75],"apply":[77],"attention":[79,120],"final":[83],"heat":[84],"improve":[87,123],"image":[89],"representation.":[91],"optimize":[95],"series":[97],"loss":[99],"functions":[100],"train":[102],"LHFNet":[103],"effectively.":[104],"Through":[105],"research":[107],"in":[108,153],"paper,":[110],"we":[111],"demonstrate":[112],"that":[113],"greatly":[122],"LHFNet.":[127],"evaluate":[129],"our":[130],"COCO":[134],"dataset":[135],"achieve":[137],"high":[139],"accuracy":[140,157],"at":[141],"fast":[143],"speed":[144],"(Tesla":[145],"V100),":[146],"outperforms":[148],"other":[149],"methods":[152],"terms":[154],"both":[156],"efficiency.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
