{"id":"https://openalex.org/W4406415742","doi":"https://doi.org/10.1109/access.2025.3529873","title":"YOLO-UP: A High-Throughput Pest Detection Model for Dense Cotton Crops Utilizing UAV-Captured Visible Light Imagery","display_name":"YOLO-UP: A High-Throughput Pest Detection Model for Dense Cotton Crops Utilizing UAV-Captured Visible Light Imagery","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406415742","doi":"https://doi.org/10.1109/access.2025.3529873"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3529873","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3529873","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3529873","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091371305","display_name":"Chenglei Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143550","display_name":"Taylor's University","ror":"https://ror.org/0498pcx51","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210143550"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Chenglei Sun","raw_affiliation_strings":["School of Computer Science, Taylor&#x2019;s University, Subang Jaya, Selangor, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Taylor&#x2019;s University, Subang Jaya, Selangor, Malaysia","institution_ids":["https://openalex.org/I4210143550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015956355","display_name":"Afizan Azman","orcid":"https://orcid.org/0000-0002-4698-2244"},"institutions":[{"id":"https://openalex.org/I4210143550","display_name":"Taylor's University","ror":"https://ror.org/0498pcx51","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210143550"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Afizan Bin Azman","raw_affiliation_strings":["School of Computer Science, Taylor&#x2019;s University, Subang Jaya, Selangor, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Taylor&#x2019;s University, Subang Jaya, Selangor, Malaysia","institution_ids":["https://openalex.org/I4210143550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015031405","display_name":"Zaiyun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zaiyun Wang","raw_affiliation_strings":["Department of Electronics and Communications, Shandong Vocational College of Information Technology, Weifang, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communications, Shandong Vocational College of Information Technology, Weifang, Shandong, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051067688","display_name":"Xiaoxiao Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136047","display_name":"Weifang University of Science and Technology","ror":"https://ror.org/04ha2bb10","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136047"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxiao Gao","raw_affiliation_strings":["Department of Animal Science and Technology, Shandong Vocational Animal Science and Veterinary College, Weifang, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Department of Animal Science and Technology, Shandong Vocational Animal Science and Veterinary College, Weifang, Shandong, China","institution_ids":["https://openalex.org/I4210136047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114858729","display_name":"Kai Ding","orcid":"https://orcid.org/0000-0002-9371-0751"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai Ding","raw_affiliation_strings":["Department of Digital and Media, Shandong Vocational College of Information Technology, Weifang, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Department of Digital and Media, Shandong Vocational College of Information Technology, Weifang, Shandong, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5091371305"],"corresponding_institution_ids":["https://openalex.org/I4210143550"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":10.398,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.97600941,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"19937","last_page":"19945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9589999914169312,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.7500070333480835},{"id":"https://openalex.org/keywords/pest-analysis","display_name":"PEST analysis","score":0.5484772324562073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5469446778297424},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5095110535621643},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47499004006385803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41782093048095703},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3482484817504883},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10181814432144165},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07983186841011047}],"concepts":[{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.7500070333480835},{"id":"https://openalex.org/C22508944","wikidata":"https://www.wikidata.org/wiki/Q568174","display_name":"PEST analysis","level":2,"score":0.5484772324562073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5469446778297424},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5095110535621643},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47499004006385803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41782093048095703},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3482484817504883},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10181814432144165},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07983186841011047},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3529873","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3529873","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b4359d25c91f41b083a834e782b9311d","is_oa":true,"landing_page_url":"https://doaj.org/article/b4359d25c91f41b083a834e782b9311d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 19937-19945 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3529873","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3529873","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.75,"display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2288122362","https://openalex.org/W2565639579","https://openalex.org/W2598666589","https://openalex.org/W2963446712","https://openalex.org/W2963857746","https://openalex.org/W2987322772","https://openalex.org/W3102707396","https://openalex.org/W3138516171","https://openalex.org/W3167976421","https://openalex.org/W3184050708","https://openalex.org/W4205266540","https://openalex.org/W4206920043","https://openalex.org/W4226158958","https://openalex.org/W4226334005","https://openalex.org/W4229055310","https://openalex.org/W4285049420","https://openalex.org/W4294927660","https://openalex.org/W4307411363","https://openalex.org/W4321764136","https://openalex.org/W4327568706","https://openalex.org/W4327652243","https://openalex.org/W4380193689","https://openalex.org/W4380357079","https://openalex.org/W4380991472","https://openalex.org/W4382600685","https://openalex.org/W4384338648","https://openalex.org/W4385431668","https://openalex.org/W4385748583","https://openalex.org/W4386047745","https://openalex.org/W4386113253","https://openalex.org/W4386175477","https://openalex.org/W4386319016","https://openalex.org/W4386463690","https://openalex.org/W4386849624","https://openalex.org/W6729983426","https://openalex.org/W6750227808","https://openalex.org/W6771062828"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Accurate":[0],"detection":[1,26,72,204],"of":[2,17,43,60,181],"pest":[3,25,71,203],"species":[4],"in":[5,27,152,159,167,205],"cotton":[6,28,80],"fields":[7,29],"is":[8,53],"vital":[9],"for":[10,202],"effective":[11,201],"agricultural":[12],"management":[13],"and":[14,23,62,98,127,161,177,183,193],"the":[15,40,57,100,106,111,114],"development":[16],"pest-resistant":[18],"crops.":[19],"However,":[20],"achieving":[21],"high-throughput":[22],"precise":[24],"remains":[30],"a":[31,69,78,89,147,154,162,194],"challenging":[32],"task.":[33],"Although":[34],"unmanned":[35],"aerial":[36],"vehicle":[37],"(UAV)":[38],"enable":[39],"rapid":[41],"acquisition":[42],"extensive":[44],"crop":[45,207],"images,":[46],"detecting":[47],"pests":[48,61],"accurately":[49],"from":[50],"these":[51],"images":[52],"difficult":[54],"due":[55],"to":[56,93,104,117,132,175],"small":[58],"size":[59],"background":[63],"interference.":[64],"This":[65],"study":[66],"introduces":[67],"YOLO-PEST,":[68],"novel":[70],"model":[73,112],"based":[74],"on":[75],"YOLOv8n,":[76],"utilizing":[77],"personal":[79],"field":[81],"imagery":[82],"dataset":[83],"acquired":[84],"by":[85],"UAVs.":[86],"YOLO-PEST":[87,141,169,189],"incorporates":[88],"custom-designed":[90],"SC3":[91],"module":[92],"enhance":[94],"low-level":[95],"feature":[96,122,135],"extraction":[97],"employs":[99],"GeLU":[101],"activation":[102],"function":[103],"address":[105],"vanishing":[107],"gradient":[108],"issue.":[109],"Additionally,":[110],"optimizes":[113],"neck":[115],"design":[116],"re-duce":[118],"semantic":[119],"discrepancies":[120],"between":[121],"layers,":[123],"improving":[124],"small-target":[125],"detection,":[126],"integrates":[128],"large-kernel":[129],"separable":[130],"convolutions":[131],"bolster":[133],"high-level":[134],"processing.":[136],"Experimental":[137],"results":[138],"demonstrate":[139],"that":[140],"outperforms":[142],"original":[143],"YOLOv8n":[144],"models,":[145],"with":[146,179],"3.46":[148],"percentage":[149,156,164,185],"points":[150,157,165],"increase":[151,158,166],"mAP50,":[153],"5.16":[155],"Precision,":[160],"7.81":[163],"Recall.":[168],"also":[170],"shows":[171],"superior":[172],"Precision":[173],"compared":[174],"DenseNet":[176],"FasterNet,":[178],"improvements":[180],"1.14":[182],"6.13":[184],"points,":[186],"respectively.":[187],"Overall,":[188],"offers":[190],"high":[191],"accuracy":[192],"compact":[195],"parameter":[196],"footprint,":[197],"making":[198],"it":[199],"highly":[200],"UAV-acquired":[206],"images.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}
