{"id":"https://openalex.org/W4415688895","doi":"https://doi.org/10.32604/cmc.2025.072494","title":"MFF-YOLO: A Target Detection Algorithm for UAV Aerial Photography","display_name":"MFF-YOLO: A Target Detection Algorithm for UAV Aerial Photography","publication_year":2025,"publication_date":"2025-10-30","ids":{"openalex":"https://openalex.org/W4415688895","doi":"https://doi.org/10.32604/cmc.2025.072494"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.072494","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.072494","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"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":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.072494","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009730590","display_name":"Dike Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dike Chen","raw_affiliation_strings":["CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101596000","display_name":"Zhiyong Qin","orcid":"https://orcid.org/0000-0001-7077-5491"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Qin","raw_affiliation_strings":["CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329264","display_name":"Ji Zhang","orcid":"https://orcid.org/0000-0002-3122-3106"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Zhang","raw_affiliation_strings":["CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China","institution_ids":["https://openalex.org/I4210153482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100747741","display_name":"Hongyuan Wang","orcid":"https://orcid.org/0000-0003-1236-6141"},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyuan Wang","raw_affiliation_strings":["CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CI Xbot School, Changzhou University, Changzhou, 213164, China 2 School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou, 213164, China 3 School of Safety Science and Engineering, Changzhou University, Changzhou, 213164, China","institution_ids":["https://openalex.org/I4210153482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210153482"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2618651,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"86","issue":"2","first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8052999973297119,"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":0.8052999973297119,"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":0.0568000003695488,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.04320000112056732,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6651999950408936},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6385999917984009},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5479999780654907},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5349000096321106},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5267000198364258},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5040000081062317},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.48890000581741333},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.414000004529953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348999977111816},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6651999950408936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6406000256538391},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6385999917984009},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5479999780654907},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5349000096321106},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5267000198364258},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5040000081062317},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48730000853538513},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39719998836517334},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.3686000108718872},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3646000027656555},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.36039999127388},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C133214962","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial photography","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2599000036716461}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.072494","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.072494","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"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":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.072494","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.072494","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"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":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0,106],"address":[1],"the":[2,50,57,99,114,130,146],"challenges":[3],"of":[4,77,102],"small":[5,103],"target":[6],"detection":[7,166],"and":[8,24,56,80,125,154],"significant":[9],"scale":[10],"variations":[11],"in":[12,140,168],"unmanned":[13],"aerial":[14,17,170],"vehicle":[15],"(UAV)":[16],"imagery,":[18],"which":[19],"often":[20],"lead":[21],"to":[22,64,97,120],"missed":[23],"false":[25],"detections,":[26],"we":[27,85,112],"propose":[28],"Multi-scale":[29,44],"Feature":[30,45,60],"Fusion":[31,46,61],"YOLO":[32],"(MFF-YOLO),":[33],"an":[34,88],"enhanced":[35],"algorithm":[36],"based":[37],"on":[38,129],"YOLOv8s.":[39],"Our":[40],"approach":[41],"introduces":[42],"a":[43,137],"Strategy":[47],"(MFFS),":[48],"comprising":[49],"Multiple":[51],"Features":[52],"C2f":[53],"(MFC)":[54],"module":[55],"Scale":[58],"Sequence":[59],"(SSFF)":[62],"module,":[63],"improve":[65],"feature":[66],"integration":[67],"across":[68],"different":[69],"network":[70],"levels.":[71],"This":[72],"enables":[73],"more":[74],"effective":[75],"capture":[76],"fine-grained":[78],"details":[79],"sequential":[81],"multi-scale":[82],"features.":[83],"Furthermore,":[84],"incorporate":[86],"Inner-CIoU,":[87],"improved":[89],"loss":[90],"function":[91],"that":[92,134,161],"uses":[93],"auxiliary":[94],"bounding":[95],"boxes":[96],"enhance":[98],"regression":[100],"quality":[101],"object":[104],"boxes.":[105],"ensure":[107],"practicality":[108],"for":[109],"UAV":[110,169],"deployment,":[111],"apply":[113],"Layer-adaptive":[115],"Magnitude-based":[116],"pruning":[117],"(LAMP)":[118],"method":[119,163],"significantly":[121],"reduce":[122],"model":[123],"size":[124],"computational":[126],"cost.":[127],"Experiments":[128],"VisDrone2019":[131],"dataset":[132],"show":[133],"MFF-YOLO":[135],"achieves":[136],"5.7%":[138],"increase":[139],"mean":[141],"average":[142],"precision":[143],"(mAP)":[144],"over":[145],"baseline,":[147],"while":[148],"reducing":[149],"parameters":[150],"by":[151,156],"8.5":[152],"million":[153],"computation":[155],"17.5%.":[157],"The":[158],"results":[159],"demonstrate":[160],"our":[162],"effectively":[164],"improves":[165],"performance":[167],"scenarios.":[171]},"counts_by_year":[],"updated_date":"2026-06-25T06:16:34.145877","created_date":"2025-10-30T00:00:00"}