{"id":"https://openalex.org/W4386361208","doi":"https://doi.org/10.1109/agro-geoinformatics59224.2023.10233526","title":"A lightweight model based on YOLOv8n in wheat spike detection","display_name":"A lightweight model based on YOLOv8n in wheat spike detection","publication_year":2023,"publication_date":"2023-07-25","ids":{"openalex":"https://openalex.org/W4386361208","doi":"https://doi.org/10.1109/agro-geoinformatics59224.2023.10233526"},"language":"en","primary_location":{"id":"doi:10.1109/agro-geoinformatics59224.2023.10233526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/agro-geoinformatics59224.2023.10233526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","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/A5042363436","display_name":"Xuyang Ban","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuyang Ban","raw_affiliation_strings":["Anhui University,School of Electronics and Information Engineering.,Hefei,China","School of Electronics and Information Engineering., Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui University,School of Electronics and Information Engineering.,Hefei,China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"School of Electronics and Information Engineering., Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100713390","display_name":"Pan Liu","orcid":"https://orcid.org/0000-0002-4063-9605"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Liu","raw_affiliation_strings":["Anhui University,School of Electronics and Information Engineering.,Hefei,China","School of Electronics and Information Engineering., Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui University,School of Electronics and Information Engineering.,Hefei,China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"School of Electronics and Information Engineering., Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025594135","display_name":"Lei Xu","orcid":"https://orcid.org/0000-0002-8499-0448"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Xu","raw_affiliation_strings":["Anhui University,School of Electronics and Information Engineering.,Hefei,China","School of Electronics and Information Engineering., Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui University,School of Electronics and Information Engineering.,Hefei,China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"School of Electronics and Information Engineering., Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100623275","display_name":"Jinling Zhao","orcid":"https://orcid.org/0000-0002-8352-7689"},"institutions":[{"id":"https://openalex.org/I140221134","display_name":"Anhui Agricultural University","ror":"https://ror.org/0327f3359","country_code":"CN","type":"education","lineage":["https://openalex.org/I140221134"]},{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinling Zhao","raw_affiliation_strings":["Anhui University,Anhui Engineering Laboratory of Agro-Ecological Big Data.,Hefei,China","Anhui Engineering Laboratory of Agro-Ecological Big Data., Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui University,Anhui Engineering Laboratory of Agro-Ecological Big Data.,Hefei,China","institution_ids":["https://openalex.org/I143868143","https://openalex.org/I140221134"]},{"raw_affiliation_string":"Anhui Engineering Laboratory of Agro-Ecological Big Data., Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042363436"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":3.3041,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91717544,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9635000228881836,"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/T12486","display_name":"Food Supply Chain Traceability","score":0.9510999917984009,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food 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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6674243807792664},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5379515290260315},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4701904058456421},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.46364039182662964},{"id":"https://openalex.org/keywords/winter-wheat","display_name":"Winter wheat","score":0.4319368004798889},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3616769313812256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34517210721969604},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28155046701431274},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21157491207122803},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14466944336891174},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.11625158786773682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6674243807792664},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5379515290260315},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4701904058456421},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.46364039182662964},{"id":"https://openalex.org/C3018661444","wikidata":"https://www.wikidata.org/wiki/Q6977574","display_name":"Winter wheat","level":2,"score":0.4319368004798889},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3616769313812256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34517210721969604},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28155046701431274},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21157491207122803},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14466944336891174},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.11625158786773682},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/agro-geoinformatics59224.2023.10233526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/agro-geoinformatics59224.2023.10233526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334897","display_name":"Natural Science Foundation of Anhui Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2153959503","https://openalex.org/W2527417112","https://openalex.org/W2527659823","https://openalex.org/W2616247523","https://openalex.org/W2833806103","https://openalex.org/W2901871634","https://openalex.org/W3102564565","https://openalex.org/W3191773007","https://openalex.org/W4214866155","https://openalex.org/W4281707986","https://openalex.org/W4285116704","https://openalex.org/W4288987532","https://openalex.org/W4292794316","https://openalex.org/W4293737653"],"related_works":["https://openalex.org/W842789846","https://openalex.org/W2031193684","https://openalex.org/W2046435967","https://openalex.org/W4231775656","https://openalex.org/W816774663","https://openalex.org/W2065300082","https://openalex.org/W247266546","https://openalex.org/W2565699560","https://openalex.org/W2351938575","https://openalex.org/W2388359778"],"abstract_inverted_index":{"Wheat":[0,22,172],"is":[1,66,81,151,176,190,198,213,231,238,261],"a":[2,309,413],"major":[3],"cereal":[4],"crop":[5],"in":[6,17,147,192,225,305,364,403,412],"China,":[7],"and":[8,11,29,35,43,70,77,90,103,123,166,181,186,196,203,210,219,236,263,266,296,328,343,350,357,376],"its":[9],"yield":[10,45,411],"quality":[12],"play":[13],"an":[14,337],"important":[15],"role":[16],"ensuring":[18],"national":[19],"food":[20],"security.":[21],"ears":[23,95,224,295],"are":[24,47,58,108,128,278],"the":[25,91,99,148,155,162,179,201,204,217,226,228,241,251,257,264,288,299,303,306,316,319,323,331,344,368,372,379,384,387,389,404,409],"key":[26],"to":[27,75,84,142,153,216,249,395],"predicting":[28],"evaluating":[30],"wheat":[31,37,44,63,65,80,94,106,223,294,400,410],"yields,":[32],"so":[33],"fast":[34],"accurate":[36],"ear":[38],"detection":[39,112,145,159,244,289,381,402],"on":[40,98,133,287],"mobile":[41,396],"devices":[42,135,397],"counting":[46,146],"of":[48,93,105,157,164,222,253,290,293,325,341,348,374],"great":[49],"importance":[50],"for":[51,131,136,240,280,398],"modern,":[52],"intelligent":[53],"agricultural":[54],"mass":[55],"production.":[56],"There":[57],"many":[59],"problems":[60,115],"with":[61,206,246,275,308],"detecting":[62],"ears:":[64],"densely":[67],"distributed,":[68],"overlapping":[69],"obscuring":[71],"each":[72],"other,":[73],"leading":[74],"error":[76],"miss":[78],"detection;":[79],"not":[82,129],"easy":[83],"distinguish":[85],"from":[86],"complex":[87],"weed":[88],"backgrounds;":[89],"appearance":[92],"varies":[96],"depending":[97],"growth":[100],"period,":[101],"color":[102],"type":[104],"they":[107],"in.":[109],"Existing":[110],"target":[111,273],"algorithms":[113],"have":[114],"such":[116],"as":[117,178,200],"large":[118],"models,":[119],"high":[120],"computing":[121],"requirements":[122],"long":[124],"computation":[125,167],"times,":[126],"which":[127,189,270,283,406],"suitable":[130],"configuration":[132],"portable":[134],"real-time":[137,144,399],"field":[138],"calculations.":[139],"In":[140,386],"order":[141],"achieve":[143],"field,":[149,405],"it":[150,237],"crucial":[152],"ensure":[154],"accuracy":[156,339],"model":[158,194,208,300,320,326,345,369,380,390],"while":[160],"reducing":[161],"number":[163,324,347,373],"parameters":[165,349,375],"time.In":[168],"this":[169,365],"paper,":[170],"Global":[171],"Head":[173],"Detection":[174],"(GWHD)":[175],"selected":[177],"dataset,":[180,227],"after":[182,233],"comparing":[183],"YOLOv5,":[184],"YOLOv7,":[185],"YOLOv8,":[187,188],"superior":[191],"comprehensive":[193],"size":[195,221],"accuracy,":[197],"chosen":[199],"baseline,":[202],"n-model":[205],"smaller":[207],"depth":[209],"convolution":[211],"channel":[212],"selected.":[214],"Due":[215],"dense":[218],"small":[220,254,291],"feature":[229,259,268,281],"information":[230,252,274],"lost":[232],"repeated":[234],"downsampling,":[235,277],"difficult":[239],"P5":[242,258],"layer":[243,260],"head":[245],"lower":[247],"resolution":[248],"detect":[250],"targets.":[255],"Therefore,":[256],"removed,":[262],"P3":[265],"P4":[267],"layers,":[269],"contain":[271],"more":[272,286],"less":[276],"used":[279],"extraction,":[282],"can":[284,391,407],"focus":[285],"targets":[292],"also":[297],"reduce":[298],"size.":[301],"Replacing":[302],"Conv":[304],"network":[307],"lightweight":[310],"convolutional":[311],"layer,":[312],"Depthwise":[313],"Conv,":[314],"lightens":[315],"model,":[317],"reduces":[318,367],"size,":[321,346,370],"decreases":[322,371],"parameters,":[327],"speeds":[329,377],"up":[330,378],"detection.":[332],"The":[333,360],"improved":[334,361],"method":[335,362],"achieves":[336],"average":[338],"(mAP@0.5)":[340],"94.3%,":[342],"FPS":[351],"reach":[352],"3.19":[353],"MB,":[354],"6.2":[355],"GFLOPs":[356],"300,":[358],"respectively.":[359],"proposed":[363],"paper":[366],"without":[382],"degrading":[383],"accuracy.":[385],"future,":[388],"be":[392],"further":[393],"deployed":[394],"spike":[401],"predict":[408],"certain":[414],"area.":[415]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
