{"id":"https://openalex.org/W4390270229","doi":"https://doi.org/10.3390/s24010134","title":"Small Target-YOLOv5: Enhancing the Algorithm for Small Object Detection in Drone Aerial Imagery Based on YOLOv5","display_name":"Small Target-YOLOv5: Enhancing the Algorithm for Small Object Detection in Drone Aerial Imagery Based on YOLOv5","publication_year":2023,"publication_date":"2023-12-26","ids":{"openalex":"https://openalex.org/W4390270229","doi":"https://doi.org/10.3390/s24010134","pmid":"https://pubmed.ncbi.nlm.nih.gov/38202996"},"language":"en","primary_location":{"id":"doi:10.3390/s24010134","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24010134","pdf_url":"https://www.mdpi.com/1424-8220/24/1/134/pdf?version=1703587931","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://www.mdpi.com/1424-8220/24/1/134/pdf?version=1703587931","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101594214","display_name":"Jiachen Zhou","orcid":"https://orcid.org/0000-0002-6900-8751"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Zhou","raw_affiliation_strings":["School of General Aviation, Nanchang Hangkong University, Nanchang 330063, China","School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of General Aviation, Nanchang Hangkong University, Nanchang 330063, China","institution_ids":["https://openalex.org/I927504317"]},{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002657825","display_name":"Taoyong Su","orcid":"https://orcid.org/0000-0001-8282-9899"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Taoyong Su","raw_affiliation_strings":["School of General Aviation, Nanchang Hangkong University, Nanchang 330063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of General Aviation, Nanchang Hangkong University, Nanchang 330063, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102006838","display_name":"Kewei Li","orcid":"https://orcid.org/0000-0001-8993-8932"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kewei Li","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China","institution_ids":["https://openalex.org/I927504317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035348844","display_name":"Jiyang Dai","orcid":"https://orcid.org/0000-0002-7854-1515"},"institutions":[{"id":"https://openalex.org/I927504317","display_name":"Nanchang Hangkong University","ror":"https://ror.org/0369pvp92","country_code":"CN","type":"education","lineage":["https://openalex.org/I927504317"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiyang Dai","raw_affiliation_strings":["School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China","institution_ids":["https://openalex.org/I927504317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002657825"],"corresponding_institution_ids":["https://openalex.org/I927504317"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":3.9078,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.95260486,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"24","issue":"1","first_page":"134","last_page":"134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T11133","display_name":"UAV Applications and Optimization","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.9879999756813049,"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":0.7628772258758545},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7235658764839172},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6923040151596069},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6274218559265137},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.6063716411590576},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5653905868530273},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.55162113904953},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5008125305175781},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.49869465827941895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4835934042930603},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43641093373298645},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.43153107166290283},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4107828140258789},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2145763337612152},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12477931380271912}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628772258758545},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7235658764839172},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6923040151596069},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6274218559265137},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.6063716411590576},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5653905868530273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.55162113904953},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5008125305175781},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.49869465827941895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4835934042930603},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43641093373298645},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.43153107166290283},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4107828140258789},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2145763337612152},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12477931380271912},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24010134","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24010134","pdf_url":"https://www.mdpi.com/1424-8220/24/1/134/pdf?version=1703587931","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:38202996","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38202996","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:pubmedcentral.nih.gov:10781303","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10781303","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10781303/pdf/sensors-24-00134.pdf","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"},{"id":"pmh:oai:doaj.org/article:40f880844adb486293a63e196e74a943","is_oa":true,"landing_page_url":"https://doaj.org/article/40f880844adb486293a63e196e74a943","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 24, Iss 1, p 134 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24010134","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24010134","pdf_url":"https://www.mdpi.com/1424-8220/24/1/134/pdf?version=1703587931","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":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4390270229.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1503780554","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W2005750530","https://openalex.org/W2150500089","https://openalex.org/W2193145675","https://openalex.org/W2565639579","https://openalex.org/W2884585870","https://openalex.org/W2962858109","https://openalex.org/W2963037989","https://openalex.org/W2963604034","https://openalex.org/W2963857746","https://openalex.org/W3004732066","https://openalex.org/W3016641475","https://openalex.org/W3034971973","https://openalex.org/W3047731328","https://openalex.org/W3106250896","https://openalex.org/W3171660447","https://openalex.org/W3208970891","https://openalex.org/W3210997132","https://openalex.org/W4212883601","https://openalex.org/W4304172678","https://openalex.org/W4306916543","https://openalex.org/W4313561323","https://openalex.org/W4319789280","https://openalex.org/W4377091754","https://openalex.org/W4382133590","https://openalex.org/W4382940613","https://openalex.org/W4386076325"],"related_works":["https://openalex.org/W2972256598","https://openalex.org/W4388964477","https://openalex.org/W4388813151","https://openalex.org/W2610408157","https://openalex.org/W4387801831","https://openalex.org/W4221156520","https://openalex.org/W2099047584","https://openalex.org/W2612465689","https://openalex.org/W4327521163","https://openalex.org/W4237245474"],"abstract_inverted_index":{"Object":[0],"detection":[1,39,60,81,112,146],"in":[2,22,47,127,143,200,205,223],"drone":[3,48,58],"aerial":[4],"imagery":[5],"has":[6],"been":[7],"a":[8,26,57,85,140,218],"consistent":[9],"focal":[10],"point":[11,221],"of":[12,29,94,148,236],"research.":[13],"Aerial":[14],"images":[15],"present":[16],"more":[17],"intricate":[18],"backgrounds,":[19],"greater":[20],"variation":[21],"object":[23,38,59],"scale,":[24,129],"and":[25,83,98,108,123,130,174,181],"higher":[27],"occurrence":[28],"small":[30,175],"objects":[31],"compared":[32,164,184],"to":[33,115,165,185,195,207,214],"standard":[34],"images.":[35],"Consequently,":[36],"conventional":[37],"algorithms":[40],"are":[41],"often":[42],"unsuitable":[43],"for":[44,171],"direct":[45],"application":[46],"scenarios.":[49],"To":[50],"address":[51],"these":[52],"challenges,":[53],"this":[54],"study":[55],"proposes":[56],"algorithm":[61],"model":[62],"based":[63],"on":[64,135],"YOLOv5,":[65],"named":[66],"SMT-YOLOv5":[67],"(Small":[68],"Target-YOLOv5).":[69],"The":[70,209],"enhancement":[71,231],"strategy":[72,152],"involves":[73],"improving":[74],"the":[75,92,95,117,136,144,157,166,186,191,196,234,237],"feature":[76,88,105],"fusion":[77],"network":[78],"by":[79,160,178],"incorporating":[80],"layers":[82],"implementing":[84],"weighted":[86],"bidirectional":[87],"pyramid":[89],"network.":[90],"Additionally,":[91],"introduction":[93],"Combine":[96],"Attention":[97],"Receptive":[99],"Fields":[100],"Block":[101],"(CARFB)":[102],"receptive":[103,118],"field":[104],"extraction":[106],"module":[107],"DyHead":[109],"dynamic":[110],"target":[111,145],"head":[113],"aims":[114],"broaden":[116],"field,":[119],"mitigate":[120],"information":[121],"loss,":[122],"enhance":[124],"perceptual":[125],"capabilities":[126],"spatial,":[128],"task":[131],"domains.":[132],"Experimental":[133],"validation":[134],"VisDrone2021":[137],"dataset":[138],"confirms":[139],"significant":[141],"improvement":[142,151,193,238],"accuracy":[147],"SMT-YOLOv5.":[149],"Each":[150],"yields":[153],"effective":[154],"results,":[155],"raising":[156],"average":[158,224],"precision":[159],"12.4":[161],"percentage":[162,220],"points":[163],"original":[167,187],"method.":[168,188],"Detection":[169],"improvements":[170],"large,":[172],"medium,":[173],"targets":[176],"increase":[177,222],"6.9%,":[179],"9.5%,":[180],"7.7%,":[182],"respectively,":[183],"Similarly,":[189],"applying":[190],"same":[192],"strategies":[194],"low-complexity":[197],"YOLOv8n":[198],"results":[199,210],"SMT-YOLOv8n,":[201,215],"which":[202],"is":[203],"comparable":[204],"complexity":[206],"SMT-YOLOv5s.":[208],"indicate":[211],"that,":[212],"relative":[213],"SMT-YOLOv5s":[216],"achieves":[217],"2.5":[219],"precision.":[225],"Furthermore,":[226],"comparative":[227],"experiments":[228],"with":[229],"other":[230],"methods":[232],"demonstrate":[233],"effectiveness":[235],"strategies.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":12}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
