{"id":"https://openalex.org/W4416250176","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227202","title":"STPYOLO: A Lightweight and Efficient Model for Small Target Pest Detection","display_name":"STPYOLO: A Lightweight and Efficient Model for Small Target Pest Detection","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250176","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227202"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031831121","display_name":"Jianyi Wang","orcid":"https://orcid.org/0009-0002-6006-7592"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyi Wang","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Xinjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Xinjiang,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100684818","display_name":"Zhenhong Jia","orcid":"https://orcid.org/0009-0006-1072-8646"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhong Jia","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Xinjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Xinjiang,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019271401","display_name":"Gang Zhou","orcid":"https://orcid.org/0000-0001-8633-6290"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Zhou","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Xinjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Xinjiang,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088209905","display_name":"Jiajia Wang","orcid":"https://orcid.org/0000-0001-7624-8430"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajia Wang","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Xinjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Xinjiang,China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047642541","display_name":"Ao Guo","orcid":"https://orcid.org/0009-0009-4622-5655"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Guo","raw_affiliation_strings":["Xinjiang University,School of Computer Science and Technology,Xinjiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University,School of Computer Science and Technology,Xinjiang,China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22005286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9409999847412109,"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":0.9409999847412109,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.011699999682605267,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.009700000286102295,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pest-analysis","display_name":"PEST analysis","score":0.7698000073432922},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4332999885082245},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4237000048160553},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4049000144004822},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.3903000056743622},{"id":"https://openalex.org/keywords/pest-control","display_name":"Pest control","score":0.32260000705718994}],"concepts":[{"id":"https://openalex.org/C22508944","wikidata":"https://www.wikidata.org/wiki/Q568174","display_name":"PEST analysis","level":2,"score":0.7698000073432922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47839999198913574},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C540442320","wikidata":"https://www.wikidata.org/wiki/Q2306047","display_name":"Pest control","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.32089999318122864},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30250000953674316},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.27300000190734863},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2887172576","https://openalex.org/W2963037989","https://openalex.org/W3107349070","https://openalex.org/W4285085541","https://openalex.org/W4307372257","https://openalex.org/W4313646799","https://openalex.org/W4318953537","https://openalex.org/W4382204431","https://openalex.org/W4386076325","https://openalex.org/W4386596896","https://openalex.org/W4386906292","https://openalex.org/W4389913818","https://openalex.org/W4390743321","https://openalex.org/W4392201638","https://openalex.org/W4396545724","https://openalex.org/W4401470611","https://openalex.org/W4402727675","https://openalex.org/W4403770406"],"related_works":[],"abstract_inverted_index":{"Vision-based":[0],"pest":[1,41,44,66,117,122,189,199],"detection":[2,13,23,45,173,190,200],"is":[3,58,124,147,175],"an":[4,167],"important":[5],"task":[6],"in":[7],"smart":[8],"agriculture.":[9],"However,":[10],"existing":[11,35],"visual":[12],"algorithms":[14],"for":[15,38,112,202],"small":[16,39],"target":[17,40],"pests":[18,95],"often":[19],"suffer":[20],"from":[21],"low":[22],"accuracy,":[24],"high":[25],"complexity,":[26],"and":[27,140,151,191],"insufficient":[28],"generalisation.":[29],"In":[30],"order":[31],"to":[32,87,130,165,195],"solve":[33],"these":[34],"algorithms\u2019":[36],"deficiencies":[37],"detection.":[42],"A":[43],"model":[46,57,86,145,185],"Small":[47],"Target":[48],"Pest":[49],"YOLO":[50],"(STPYOLO)":[51],"based":[52],"on":[53,90,136,159],"the":[54,62,85,101,104,113,141,152,160,183,187,197],"improved":[55],"YOLOv10":[56],"proposed.":[59],"To":[60,110],"enhance":[61],"performance":[63,135,174],"of":[64,103,115,154,169],"small-target":[65,94,116,121],"detection,":[67],"this":[68],"paper":[69],"introduces":[70],"a":[71,119],"novel":[72],"feature":[73,82],"fusion":[74],"method":[75,79],"called":[76],"MicroTargetScaleFusion(MTSFusion).":[77],"This":[78],"finely":[80],"adjusts":[81],"weights,":[83],"allowing":[84],"better":[88],"focus":[89],"key":[91],"areas":[92],"where":[93],"are":[96],"located.":[97],"It":[98],"also":[99],"reduces":[100],"complexity":[102],"model,":[105],"making":[106],"it":[107],"more":[108],"lightweight.":[109],"compensate":[111],"lack":[114],"datasets,":[118],"self-constructed":[120],"dataset":[123,162],"built,":[125],"including":[126],"six":[127],"pests.":[128],"Compared":[129],"YOLOv10,":[131],"STPYOLO":[132,184],"shows":[133],"strong":[134],"two":[137],"public":[138],"datasets":[139],"self-built":[142,161],"dataset.":[143],"The":[144,171],"size":[146],"reduced":[148],"by":[149,156],"36.2%,":[150],"number":[153],"parameters":[155],"40%.":[157],"Meanwhile":[158],"mAP50":[163],"increased":[164],"72.6%,":[166],"improvement":[168],"5.8%.":[170],"excellent":[172],"still":[176],"maintained":[177],"while":[178],"lightweighting.":[179],"Finally,":[180],"we":[181],"integrated":[182],"into":[186],"designed":[188],"early":[192],"warning":[193],"system":[194],"realize":[196],"real-time":[198],"function":[201],"farm":[203],"cotton":[204],"fields.":[205]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-14T00:00:00"}