{"id":"https://openalex.org/W3159727287","doi":"https://doi.org/10.32604/jihpp.2021.010065","title":"Feature-Enhanced RefineDet: Fast Detection of Small Objects","display_name":"Feature-Enhanced RefineDet: Fast Detection of Small Objects","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3159727287","doi":"https://doi.org/10.32604/jihpp.2021.010065","mag":"3159727287"},"language":"en","primary_location":{"id":"doi:10.32604/jihpp.2021.010065","doi":"https://doi.org/10.32604/jihpp.2021.010065","is_oa":true,"landing_page_url":"https://doi.org/10.32604/jihpp.2021.010065","pdf_url":null,"source":{"id":"https://openalex.org/S4210183694","display_name":"Journal of Information Hiding and Privacy Protection","issn_l":"2637-4226","issn":["2637-4226","2637-4234"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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 Information Hiding and Privacy Protection","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/jihpp.2021.010065","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100671317","display_name":"Lei Zhao","orcid":"https://orcid.org/0000-0002-8309-9776","observed_orcids":["https://orcid.org/0000-0002-8309-9776"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lei Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101521257","display_name":"Ming Zhao","orcid":"https://orcid.org/0000-0002-1310-6766","observed_orcids":["https://orcid.org/0000-0002-1310-6766"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100671317"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.36,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.53534095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":"1","first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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":0.9990000128746033,"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":0.0003000000142492354,"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":0.00019999999494757503,"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/small-object-detection","display_name":"small object detection","score":0.9990000128746033},{"id":"https://openalex.org/keywords/receptive-field-block","display_name":"receptive field block","score":0.8759999871253967},{"id":"https://openalex.org/keywords/multiscale-feature-fusion","display_name":"multi-scale feature fusion","score":0.8059999942779541},{"id":"https://openalex.org/keywords/low-level-features","display_name":"low-level features","score":0.7710000276565552},{"id":"https://openalex.org/keywords/speed-accuracy-trade-off","display_name":"speed-accuracy trade-off","score":0.7429999709129333},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.6309999823570251}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.669743537902832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5713775157928467},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.53301602602005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4883434474468231},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4014100730419159},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/jihpp.2021.010065","doi":"https://doi.org/10.32604/jihpp.2021.010065","is_oa":true,"landing_page_url":"https://doi.org/10.32604/jihpp.2021.010065","pdf_url":null,"source":{"id":"https://openalex.org/S4210183694","display_name":"Journal of Information Hiding and Privacy Protection","issn_l":"2637-4226","issn":["2637-4226","2637-4234"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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 Information Hiding and Privacy Protection","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/jihpp.2021.010065","doi":"https://doi.org/10.32604/jihpp.2021.010065","is_oa":true,"landing_page_url":"https://doi.org/10.32604/jihpp.2021.010065","pdf_url":null,"source":{"id":"https://openalex.org/S4210183694","display_name":"Journal of Information Hiding and Privacy Protection","issn_l":"2637-4226","issn":["2637-4226","2637-4234"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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 Information Hiding and Privacy Protection","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4378469551","https://openalex.org/W3194350182","https://openalex.org/W2890785584","https://openalex.org/W7125585713","https://openalex.org/W4281675780","https://openalex.org/W4410193147","https://openalex.org/W3086040666","https://openalex.org/W4312334708","https://openalex.org/W4406138448","https://openalex.org/W4390272074"],"abstract_inverted_index":{"Object":[0],"detection":[1,175,208],"has":[2,12],"been":[3],"studied":[4],"for":[5,56,164],"many":[6],"years.":[7],"The":[8],"convolutional":[9],"neural":[10],"network":[11,98,103,152],"made":[13],"great":[14],"progress":[15],"in":[16,51,206],"the":[17,27,34,41,67,72,75,85,96,113,123,130,151,155,159,162,169,172,179,187,207],"accuracy":[18,170],"and":[19,33,89,127,161,168],"speed":[20,126],"of":[21,30,36,40,74,87,115,125,157,171,209],"object":[22,117],"detection.":[23],"However,":[24],"due":[25],"to":[26,46,61,70,111,121,194],"low":[28],"resolution":[29],"small":[31,49,57,116,173,210],"objects":[32,50],"representation":[35],"fuzzy":[37],"features,":[38,148],"one":[39,59],"challenges":[42],"now":[43],"is":[44,60,69,182],"how":[45],"effectively":[47],"detect":[48],"images.":[52],"Existing":[53],"target":[54,166,174],"detectors":[55],"objects:":[58],"use":[62,154],"high-resolution":[63],"images":[64],"as":[65,120],"input,":[66],"other":[68,195],"increase":[71,84],"depth":[73],"CNN":[76],"network,":[77],"but":[78],"these":[79],"two":[80],"methods":[81],"will":[82],"undoubtedly":[83],"cost":[86],"calculation":[88],"time-consuming.":[90],"In":[91],"this":[92],"paper,":[93],"based":[94,177],"on":[95,178,186],"RefineDet":[97],"framework,":[99],"we":[100,133],"propose":[101,134],"our":[102,199],"structure":[104],"RF2Det":[105],"by":[106],"introducing":[107],"Receptive":[108],"Field":[109],"Block":[110],"solve":[112],"problem":[114],"detection,":[118,167],"so":[119,149],"achieve":[122],"balance":[124],"accuracy.":[128],"At":[129],"same":[131],"time,":[132],"a":[135],"Medium-level":[136],"Feature":[137],"Pyramid":[138],"Networks,":[139],"which":[140],"combines":[141],"appropriate":[142],"high-level":[143,163],"context":[144],"features":[145,156,181],"with":[146],"low-level":[147,160,180],"that":[150,192],"can":[153],"both":[158],"multi-scale":[165],"task":[176],"improved.":[183],"Extensive":[184],"experiments":[185],"MS":[188],"COCO":[189],"dataset":[190],"demonstrate":[191],"compared":[193],"most":[196],"advanced":[197],"methods,":[198],"proposed":[200],"method":[201],"shows":[202],"significant":[203],"performance":[204],"improvement":[205],"objects.":[211]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-06-24T06:17:17.354583","created_date":"2021-05-10T00:00:00"}