{"id":"https://openalex.org/W4399418475","doi":"https://doi.org/10.1145/3651671.3651769","title":"Backbone Feature Hierarchy Selection Strategy and Verification in Small Object Detection","display_name":"Backbone Feature Hierarchy Selection Strategy and Verification in Small Object Detection","publication_year":2024,"publication_date":"2024-02-02","ids":{"openalex":"https://openalex.org/W4399418475","doi":"https://doi.org/10.1145/3651671.3651769"},"language":"en","primary_location":{"id":"doi:10.1145/3651671.3651769","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3651671.3651769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 16th International Conference on Machine Learning and Computing","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/A5067734768","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0003-2511-5843"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN","HK"],"is_corresponding":true,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["Network Information Center, Xinjiang University of Political Science And Law, China, \rDepartment of Computer Science, City University of Hong Kong, China and \rSchool of Remote Sensing and Information Engineering, Wuhan University, China"],"raw_orcid":"https://orcid.org/0000-0003-2511-5843","affiliations":[{"raw_affiliation_string":"Network Information Center, Xinjiang University of Political Science And Law, China, \rDepartment of Computer Science, City University of Hong Kong, China and \rSchool of Remote Sensing and Information Engineering, Wuhan University, China","institution_ids":["https://openalex.org/I96908189","https://openalex.org/I168719708","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041554673","display_name":"M. Ronnier Luo M. Ronnier Luo","orcid":"https://orcid.org/0009-0000-4658-9453"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meizhen Luo","raw_affiliation_strings":["Academic Division, Liuzhou First Vocational and Technical School, China and \rGeneral Office, Wuhan Software Federation Intelligence United Technology Co., Ltd.\u00a0, China"],"raw_orcid":"https://orcid.org/0009-0000-4658-9453","affiliations":[{"raw_affiliation_string":"Academic Division, Liuzhou First Vocational and Technical School, China and \rGeneral Office, Wuhan Software Federation Intelligence United Technology Co., Ltd.\u00a0, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016741865","display_name":"Shankai Yan","orcid":"https://orcid.org/0000-0003-0369-4979"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shankai Yan","raw_affiliation_strings":["School of Computer Science Technology, Hainan University, China"],"raw_orcid":"https://orcid.org/0000-0003-0369-4979","affiliations":[{"raw_affiliation_string":"School of Computer Science Technology, Hainan University, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014634004","display_name":"Juan Hu","orcid":"https://orcid.org/0009-0004-0169-6131"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Juan Hu","raw_affiliation_strings":["Discipline Inspection and Supervision College, Normal University, China"],"raw_orcid":"https://orcid.org/0009-0004-0169-6131","affiliations":[{"raw_affiliation_string":"Discipline Inspection and Supervision College, Normal University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070175038","display_name":"Ling Peng","orcid":"https://orcid.org/0009-0009-6170-7230"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ling Peng","raw_affiliation_strings":["Real Estate Registration Center, Huanggang Land and Resources Bureau, China"],"raw_orcid":"https://orcid.org/0009-0009-6170-7230","affiliations":[{"raw_affiliation_string":"Real Estate Registration Center, Huanggang Land and Resources Bureau, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065833216","display_name":"Liangshun Wu","orcid":"https://orcid.org/0000-0001-6183-4680"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangshun Wu","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, China"],"raw_orcid":"https://orcid.org/0000-0001-6183-4680","affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012179706","display_name":"Y. L. Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156464","display_name":"Anhui Xinhua University","ror":"https://ror.org/053d7x641","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210156464"]},{"id":"https://openalex.org/I4400573165","display_name":"Guangzhou Xinhua University","ror":"https://ror.org/0068n3903","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujuan Wang","raw_affiliation_strings":["Guangzhou Xinhua University, China"],"raw_orcid":"https://orcid.org/0009-0001-6463-8666","affiliations":[{"raw_affiliation_string":"Guangzhou Xinhua University, China","institution_ids":["https://openalex.org/I4210156464","https://openalex.org/I4400573165"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5067734768"],"corresponding_institution_ids":["https://openalex.org/I168719708","https://openalex.org/I37461747","https://openalex.org/I96908189"],"apc_list":null,"apc_paid":null,"fwci":0.7142,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69616699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"304","last_page":"310"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9937999844551086,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9936000108718872,"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":0.7781342267990112},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7685970067977905},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.7506969571113586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7201709151268005},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6244738101959229},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6086347103118896},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5388268232345581},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5116970539093018},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5066347718238831},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48032012581825256},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4489091634750366},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44058021903038025},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4318747818470001},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.41392937302589417},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07908672094345093}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7781342267990112},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7685970067977905},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.7506969571113586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7201709151268005},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6244738101959229},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6086347103118896},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5388268232345581},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5116970539093018},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5066347718238831},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48032012581825256},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4489091634750366},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44058021903038025},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4318747818470001},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.41392937302589417},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07908672094345093},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3651671.3651769","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3651671.3651769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 16th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2799215407","https://openalex.org/W2963037989","https://openalex.org/W3160195350","https://openalex.org/W6603776078","https://openalex.org/W6608287133","https://openalex.org/W6773629745","https://openalex.org/W6777312207"],"related_works":["https://openalex.org/W2802018156","https://openalex.org/W4313315626","https://openalex.org/W2101531944","https://openalex.org/W2913302899","https://openalex.org/W2922437833","https://openalex.org/W4312696271","https://openalex.org/W4223892596","https://openalex.org/W2933098581","https://openalex.org/W2556125083","https://openalex.org/W3204901196"],"abstract_inverted_index":{"Object":[0],"detection":[1,19,30,36,44,87,163,186,208,218],"techniques":[2],"are":[3],"used":[4],"to":[5,25,81,139,154,157,166,181,188],"determine":[6],"object":[7,29,35,162,207,217],"categories":[8],"and":[9,21,32,56,192,205,225,228,231],"localization":[10],"in":[11,62,101,183],"images.":[12],"Different":[13],"tasks":[14,61],"have":[15,48,82],"different":[16],"requirements":[17],"for":[18,85,113,215],"efficiency":[20,27],"accuracy,":[22],"which":[23],"leads":[24],"high":[26,83],"one-stage":[28,204],"methods":[31],"high-precision":[33],"two-stage":[34,206],"methods.":[37],"As":[38],"the":[39,49,79,86,93,124,128,131,134,140,147,151,159,167,173,184,200,220],"main":[40],"category":[41],"of":[42,51,88,95,98,127,133,150],"difficult":[43,89],"objects,":[45],"small":[46,99,152,161,194,216],"objects":[47,100,153],"characteristics":[50],"few":[52],"pixels,":[53],"wide":[54],"distribution,":[55],"complex":[57],"background.":[58],"Many":[59],"serious":[60],"special":[63],"environments,":[64],"such":[65],"as":[66],"industrial":[67],"defect":[68],"detection,":[69],"large-scale":[70],"pedestrian":[71],"statistics,":[72],"remote":[73],"sensing":[74],"image":[75],"recognition,":[76],"etc.":[77],"require":[78],"model":[80],"accuracy":[84],"objects.":[90],"Aiming":[91],"at":[92],"problem":[94],"information":[96,196],"loss":[97],"deep":[102],"network":[103,115,223],"features,":[104],"this":[105,210],"paper":[106,211],"proposes":[107,212],"a":[108],"feature":[109,125],"levels":[110],"selection":[111],"method":[112],"backbone":[114,129,201],"based":[116],"on":[117,203],"effective":[118,135,168],"receptive":[119,136,169],"fields.":[120],"By":[121],"moving":[122],"down":[123],"level":[126,224],"network,":[130],"size":[132,171],"field":[137,170],"corresponding":[138],"selected":[141,180],"hierarchical":[142],"features":[143],"is":[144,179,197],"matched":[145],"with":[146],"scale":[148],"distribution":[149],"be":[155],"detected":[156],"obtain":[158],"best":[160],"performance.":[164],"According":[165],"(ERF),":[172],"appropriate":[174],"Shallow":[175],"Feature":[176],"Selection":[177],"(SFS)":[178],"participate":[182],"subsequent":[185],"process":[187],"ensure":[189],"that":[190],"accurate":[191],"sufficient":[193],"target":[195],"extracted":[198],"from":[199,219],"network.Based":[202],"methods,":[209],"improvement":[213],"measures":[214],"data":[221],"level,":[222,227],"training":[226],"designs":[229],"experiments":[230],"validates":[232],"them.":[233]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}