{"id":"https://openalex.org/W4406997908","doi":"https://doi.org/10.3390/computers14020044","title":"Optimizing Loss Functions for You Only Look Once Models: Improving Object Detection in Agricultural Datasets","display_name":"Optimizing Loss Functions for You Only Look Once Models: Improving Object Detection in Agricultural Datasets","publication_year":2025,"publication_date":"2025-01-30","ids":{"openalex":"https://openalex.org/W4406997908","doi":"https://doi.org/10.3390/computers14020044"},"language":"en","primary_location":{"id":"doi:10.3390/computers14020044","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14020044","pdf_url":null,"source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"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":"Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/computers14020044","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072218995","display_name":"Atsuki Matsui","orcid":null},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsuki Matsui","raw_affiliation_strings":["Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1, Nojihigashi, Kusatsu 525-8577, Shiga, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1, Nojihigashi, Kusatsu 525-8577, Shiga, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053005436","display_name":"Ryuto Ishibashi","orcid":"https://orcid.org/0009-0000-3161-2200"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuto Ishibashi","raw_affiliation_strings":["Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1, Nojihigashi, Kusatsu 525-8577, Shiga, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1, Nojihigashi, Kusatsu 525-8577, Shiga, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076579498","display_name":"Lin Meng","orcid":"https://orcid.org/0000-0003-4351-6923"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Lin Meng","raw_affiliation_strings":["College of Science and Engineering, Ritsumeikan University, 1-1-1, Nojihigashi, Kusatsu 525-8577, Shiga, Japan"],"affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Ritsumeikan University, 1-1-1, Nojihigashi, Kusatsu 525-8577, Shiga, Japan","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076579498"],"corresponding_institution_ids":["https://openalex.org/I135768898"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":2.244,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84668515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"14","issue":"2","first_page":"44","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.920799970626831,"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":0.920799970626831,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.6218472719192505},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5830707550048828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5411862730979919},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4774746894836426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34744179248809814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.20970556139945984},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17877817153930664},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.06703513860702515}],"concepts":[{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.6218472719192505},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5830707550048828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5411862730979919},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4774746894836426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34744179248809814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.20970556139945984},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17877817153930664},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.06703513860702515}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computers14020044","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14020044","pdf_url":null,"source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"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":"Computers","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ae0e8a3c65e44bdbaa4e9216fe606d16","is_oa":true,"landing_page_url":"https://doaj.org/article/ae0e8a3c65e44bdbaa4e9216fe606d16","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":"Computers, Vol 14, Iss 2, p 44 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computers14020044","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers14020044","pdf_url":null,"source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"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":"Computers","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2031489346","https://openalex.org/W2091443795","https://openalex.org/W2102605133","https://openalex.org/W2193145675","https://openalex.org/W2570343428","https://openalex.org/W2936718694","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2963430102","https://openalex.org/W2969985801","https://openalex.org/W2995726119","https://openalex.org/W2997747012","https://openalex.org/W3001083904","https://openalex.org/W3034971973","https://openalex.org/W3096609285","https://openalex.org/W3172087149","https://openalex.org/W3194790201","https://openalex.org/W4381986098","https://openalex.org/W4386076325","https://openalex.org/W4387475539","https://openalex.org/W4387490327","https://openalex.org/W6638791942","https://openalex.org/W6796016286"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4312842780","https://openalex.org/W2883677709","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Japan":[0],"faces":[1],"a":[2,45,74,97,129,167,232],"significant":[3],"labor":[4,42],"shortage":[5],"due":[6],"to":[7,47,118,147,157,169,181,198,209,230,264,273,285,300],"an":[8,159],"aging":[9],"population,":[10],"particularly":[11],"in":[12,71,132,303],"the":[13,23,30,38,67,84,87,108,148,183,206,221,228,238,245,254,267,276,288,294],"agricultural":[14,41,304],"sector.":[15],"The":[16,53,202,217],"rising":[17],"average":[18],"age":[19],"of":[20,26,32,40,76,110,223,234,259,296],"farmers":[21],"and":[22,43,63,73,82,113,125,139,172,212,275],"declining":[24],"participation":[25],"younger":[27],"individuals":[28],"threaten":[29],"sustainability":[31],"farming":[33],"practices.":[34,305],"These":[35,240,291],"trends":[36],"reduce":[37],"availability":[39],"pose":[44],"risk":[46],"lowering":[48],"Japan\u2019s":[49],"food":[50,56],"self-sufficiency":[51],"rate.":[52],"reliance":[54],"on":[55,86,287],"imports":[57],"raises":[58],"concerns":[59],"regarding":[60],"price":[61],"fluctuations":[62],"sanitation":[64],"standards.":[65],"Moreover,":[66],"challenging":[68],"working":[69],"conditions":[70],"agriculture":[72,116],"lack":[75],"technological":[77],"innovation":[78],"have":[79,242],"hindered":[80],"productivity":[81],"increased":[83,244,270],"burden":[85],"existing":[88],"workforce.":[89],"To":[90],"address":[91],"these":[92],"challenges,":[93],"\u201csmart":[94],"agriculture\u201d":[95],"presents":[96],"promising":[98],"solution.":[99],"By":[100],"leveraging":[101],"advanced":[102],"technologies":[103],"such":[104],"as":[105],"sensors,":[106],"drones,":[107],"Internet":[109],"Things":[111],"(IoT),":[112],"automation,":[114],"smart":[115],"aims":[117],"optimize":[119],"farm":[120],"operations.":[121],"Real-time":[122],"data":[123],"collection":[124],"AI-driven":[126],"analysis":[127],"play":[128],"crucial":[130],"role":[131],"monitoring":[133],"crop":[134],"growth,":[135],"assessing":[136],"soil":[137],"conditions,":[138],"improving":[140],"overall":[141],"efficiency.":[142],"This":[143,164],"study":[144],"proposes":[145],"enhancements":[146],"YOLO":[149,191],"(You":[150],"Only":[151],"Look":[152],"Once)":[153],"object":[154,235],"detection":[155,200,222,247],"model":[156,192,229],"develop":[158],"automated":[160],"tomato":[161,289],"harvesting":[162,184],"system.":[163],"system":[165,299],"uses":[166],"camera":[168],"detect":[170],"tomatoes":[171,211,225],"assess":[173],"their":[174,214],"ripeness":[175],"for":[176],"harvest.":[177],"Our":[178,189,249],"objective":[179],"is":[180],"streamline":[182],"process":[185],"through":[186],"AI":[187],"technology.":[188],"improved":[190,261],"integrates":[193],"two":[194],"novel":[195],"loss":[196],"functions":[197],"enhance":[199,301],"accuracy.":[201],"first,":[203],"\u201cVSR\u201d,":[204],"refines":[205],"model\u2019s":[207],"ability":[208],"classify":[210],"determine":[213],"harvest":[215],"readiness.":[216],"second,":[218],"\u201cSBCE\u201d,":[219],"enhances":[220],"small":[224],"by":[226],"training":[227],"recognize":[231],"range":[233],"sizes":[236],"within":[237],"dataset.":[239,290],"improvements":[241],"significantly":[243],"system\u2019s":[246],"performance.":[248],"experimental":[250],"results":[251],"demonstrate":[252],"that":[253],"mean":[255,277],"Average":[256],"Precision":[257],"(mAP)":[258],"YOLOv7-tiny":[260],"from":[262,271,283],"61.81%":[263],"70.21%.":[265],"Additionally,":[266],"F1":[268],"score":[269],"0.61":[272],"0.71":[274],"Intersection":[278],"over":[279],"Union":[280],"(mIoU)":[281],"rose":[282],"65.03%":[284],"66.44%":[286],"findings":[292],"underscore":[293],"potential":[295],"our":[297],"proposed":[298],"efficiency":[302]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
