{"id":"https://openalex.org/W4289529562","doi":"https://doi.org/10.3390/s22155719","title":"Inferior and Coordinate Distillation for Object Detectors","display_name":"Inferior and Coordinate Distillation for Object Detectors","publication_year":2022,"publication_date":"2022-07-30","ids":{"openalex":"https://openalex.org/W4289529562","doi":"https://doi.org/10.3390/s22155719","pmid":"https://pubmed.ncbi.nlm.nih.gov/35957276"},"language":"en","primary_location":{"id":"doi:10.3390/s22155719","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22155719","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/s22155719","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037739298","display_name":"Yao Zhang","orcid":"https://orcid.org/0000-0003-1273-4397"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhang","raw_affiliation_strings":["School of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":"https://orcid.org/0000-0003-1273-4397","affiliations":[{"raw_affiliation_string":"School of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447990","display_name":"Yang Li","orcid":"https://orcid.org/0000-0003-1682-0284"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["School of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":"https://orcid.org/0000-0003-1682-0284","affiliations":[{"raw_affiliation_string":"School of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037669752","display_name":"Zhisong Pan","orcid":"https://orcid.org/0000-0001-8615-7313"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhisong Pan","raw_affiliation_strings":["School of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China","institution_ids":["https://openalex.org/I4210163363"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037669752"],"corresponding_institution_ids":["https://openalex.org/I4210163363"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06961979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"15","first_page":"5719","last_page":"5719"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9934999942779541,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.992900013923645,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7862002849578857},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7397517561912537},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7182546257972717},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.695611298084259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5888822078704834},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5842035412788391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5112965106964111},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5097436308860779},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47089508175849915},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44021332263946533},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4375704824924469},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.426454097032547},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.13354846835136414},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.10753738880157471},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09457278251647949}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7862002849578857},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7397517561912537},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7182546257972717},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.695611298084259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5888822078704834},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5842035412788391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5112965106964111},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5097436308860779},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47089508175849915},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44021332263946533},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4375704824924469},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.426454097032547},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.13354846835136414},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.10753738880157471},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09457278251647949},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057168","descriptor_name":"Distillation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057168","descriptor_name":"Distillation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057168","descriptor_name":"Distillation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22155719","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22155719","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35957276","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35957276","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:df435b4bdd5444a1a97ed22b89fb7c9e","is_oa":true,"landing_page_url":"https://doaj.org/article/df435b4bdd5444a1a97ed22b89fb7c9e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 15, p 5719 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/15/5719/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22155719","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 15; Pages: 5719","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9370902","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9370902","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22155719","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22155719","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4683421875","display_name":null,"funder_award_id":"62076251","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2750784772","https://openalex.org/W2884561390","https://openalex.org/W2884585870","https://openalex.org/W2959289524","https://openalex.org/W2982770724","https://openalex.org/W3127215335","https://openalex.org/W3173270634","https://openalex.org/W3176459575","https://openalex.org/W3177196641","https://openalex.org/W4200633579","https://openalex.org/W4214524539","https://openalex.org/W4225385394","https://openalex.org/W4226426325","https://openalex.org/W4234425732","https://openalex.org/W4313141028","https://openalex.org/W6637551013","https://openalex.org/W6762585180"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W2087343574","https://openalex.org/W4390721878","https://openalex.org/W2969228573"],"abstract_inverted_index":{"Current":[0],"distillation":[1,48],"methods":[2],"only":[3],"distill":[4],"between":[5,116],"corresponding":[6],"layers,":[7,104],"and":[8,43,46,77,108,122,150,165,178],"do":[9],"not":[10],"consider":[11],"the":[12,24,28,36,56,64,69,74,79,85,89,93,100,106,114,117,124,140,170,182],"knowledge":[13,87],"contained":[14,59],"in":[15,60,82,88],"preceding":[16],"layers.":[17],"To":[18],"solve":[19],"this":[20],"problem,":[21],"we":[22],"analyzed":[23],"guiding":[25],"effect":[26],"of":[27,31,39,63,102,119],"inferior":[29,45],"features":[30,101,118],"a":[32,40],"teacher":[33,65,90],"model":[34,71],"on":[35,133],"coordinate":[37,47],"feature":[38],"student":[41,70],"model,":[42],"proposed":[44,53],"for":[49,139],"object":[50,135,154],"detectors.":[51,136],"The":[52,137],"method":[54],"utilizes":[55],"rich":[57],"information":[58,76],"different":[61,103,120,134],"layers":[62],"model;":[66],"such":[67],"that":[68],"can":[72],"review":[73],"old":[75],"learn":[78],"new":[80],"information,":[81],"addition":[83],"to":[84,98,110,169],"dark":[86],"model.":[91],"Moreover,":[92],"refine":[94],"module":[95],"is":[96],"used":[97],"align":[99],"distinguish":[105],"spatial":[107],"channel":[109],"extract":[111],"attention,":[112],"strengthen":[113],"correlation":[115],"stages,":[121],"prevent":[123],"disorder":[125],"caused":[126],"by":[127],"merging.":[128],"Exclusive":[129],"experiments":[130],"were":[131,162],"conducted":[132],"results":[138],"mean":[141],"average":[142],"precision":[143],"(mAP)":[144],"obtained":[145],"using":[146],"Faster":[147],"R-CNN,":[148],"RetinaNet,":[149],"fully":[151],"convolutional":[152],"one-stage":[153],"detector":[155],"(FCOS)":[156],"with":[157,167],"ResNet-50":[158],"as":[159],"its":[160],"backbone":[161],"40.5%,":[163],"39.8%,":[164],"42.8%":[166],"regard":[168],"COCO":[171],"dataset,":[172],"respectively;":[173],"which":[174],"are":[175],"2.1%,":[176],"2.4%,":[177],"4.3%":[179],"higher":[180],"than":[181],"benchmark,":[183],"respectively.":[184]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}