{"id":"https://openalex.org/W4408399539","doi":"https://doi.org/10.1109/lgrs.2025.3548106","title":"Fine Tuning Large Models for Straw Detection in Harvested Fields Under Few-Shot Learning Scenarios","display_name":"Fine Tuning Large Models for Straw Detection in Harvested Fields Under Few-Shot Learning Scenarios","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408399539","doi":"https://doi.org/10.1109/lgrs.2025.3548106"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2025.3548106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3548106","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5015361484","display_name":"Di Wu","orcid":"https://orcid.org/0000-0001-8473-1553"},"institutions":[{"id":"https://openalex.org/I4210161462","display_name":"Heilongjiang Institute of Technology","ror":"https://ror.org/05x0m9n95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210161462"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wu","raw_affiliation_strings":["School of Surveying and Mapping Engineering, Heilongjiang Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping Engineering, Heilongjiang Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I4210161462"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006935356","display_name":"Xi Liu","orcid":"https://orcid.org/0000-0002-0085-6250"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Liu","raw_affiliation_strings":["Heilongjiang Geomatics Centre of Ministry of Natural Resources, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heilongjiang Geomatics Centre of Ministry of Natural Resources, Harbin, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101562165","display_name":"Song Bai","orcid":"https://orcid.org/0009-0005-0279-4945"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Bai","raw_affiliation_strings":["Heilongjiang Geomatics Centre of Ministry of Natural Resources, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heilongjiang Geomatics Centre of Ministry of Natural Resources, Harbin, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110840893","display_name":"Caixia Liu","orcid":"https://orcid.org/0000-0001-5851-6374"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caixia Liu","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5851-6374","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I4210137199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.02833309,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9365000128746033,"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":0.9365000128746033,"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/shot","display_name":"Shot (pellet)","score":0.6543869376182556},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5341063737869263},{"id":"https://openalex.org/keywords/straw","display_name":"Straw","score":0.4877408444881439},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4438779652118683},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3779199421405792},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.33574506640434265},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.3348449468612671},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.17523989081382751},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.150736004114151},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14378637075424194},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.13107424974441528}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6543869376182556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5341063737869263},{"id":"https://openalex.org/C2779587293","wikidata":"https://www.wikidata.org/wiki/Q7622360","display_name":"Straw","level":2,"score":0.4877408444881439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4438779652118683},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3779199421405792},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.33574506640434265},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.3348449468612671},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.17523989081382751},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.150736004114151},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14378637075424194},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.13107424974441528},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3548106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3548106","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G4471632471","display_name":null,"funder_award_id":"2021GJ05","funder_id":"https://openalex.org/F4320338470","funder_display_name":"Science Research Foundation of Zhejiang Province"},{"id":"https://openalex.org/G561147584","display_name":null,"funder_award_id":"LH2022C076","funder_id":"https://openalex.org/F4320323085","funder_display_name":"Natural Science Foundation of Heilongjiang Province"},{"id":"https://openalex.org/G8026922857","display_name":null,"funder_award_id":"2023YFB3907702","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320323085","display_name":"Natural Science Foundation of Heilongjiang Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320338470","display_name":"Science Research Foundation of Zhejiang Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W1988252877","https://openalex.org/W2560023338","https://openalex.org/W2560311620","https://openalex.org/W2563705555","https://openalex.org/W2884436604","https://openalex.org/W2922881785","https://openalex.org/W2971419816","https://openalex.org/W3144503735","https://openalex.org/W3148765418","https://openalex.org/W3188060066","https://openalex.org/W4319163914","https://openalex.org/W4379660323","https://openalex.org/W4382240924","https://openalex.org/W4386076694","https://openalex.org/W4390878916","https://openalex.org/W4395703452","https://openalex.org/W4400881081","https://openalex.org/W6739696289","https://openalex.org/W6757817989","https://openalex.org/W6796581206"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2205760960","https://openalex.org/W2334685461","https://openalex.org/W2367726858","https://openalex.org/W2366718574","https://openalex.org/W2364501903"],"abstract_inverted_index":{"The":[0,105],"effective":[1],"monitoring":[2],"of":[3,22,53,78,120,125,144,152,159,181,190,197],"crop":[4],"residues,":[5],"particularly":[6],"straw":[7,23,74],"in":[8,162],"non-harvested":[9],"fields,":[10],"is":[11],"essential":[12],"for":[13,39],"sustainable":[14],"agricultural":[15],"practices":[16],"and":[17,36,71,103,168,203],"environmental":[18],"management.":[19],"Traditional":[20],"methods":[21],"detection":[24],"often":[25],"face":[26],"challenges":[27,189],"due":[28],"to":[29,45,69],"limited":[30,198],"training":[31,81,183],"data,":[32,184],"high":[33],"annotation":[34,170,201],"complexity,":[35],"the":[37,51,54,79,109,123,126,135,157,188,195],"need":[38],"accurate":[40],"feature":[41],"recognition.":[42],"In":[43],"response":[44],"these":[46],"challenges,":[47],"this":[48],"study":[49],"investigates":[50],"effectiveness":[52],"segment":[55],"anything":[56],"model":[57],"(SAM)-vision":[58],"transformer":[59],"(ViT)-huge-low-rank":[60],"adaptation":[61],"(LoRA)":[62],"method,":[63],"which":[64],"leverages":[65],"few-shot":[66,160],"learning":[67,161],"techniques":[68],"accurately":[70],"efficiently":[72],"identify":[73],"using":[75],"only":[76],"0.65%":[77],"available":[80],"data.":[82],"A":[83],"comparative":[84],"analysis":[85],"was":[86],"performed":[87],"under":[88],"consistent":[89],"testing":[90],"conditions":[91],"against":[92],"several":[93],"established":[94],"algorithms,":[95],"including":[96],"Deeplabv3,":[97],"FCN,":[98],"PSPNet,":[99],"TransformerUNet,":[100],"UNet3+,":[101],"AFFormer,":[102],"DynaMas.":[104],"results":[106],"indicate":[107],"that":[108],"SAM-ViT-huge-LoRA":[110],"method":[111,136],"achieves":[112],"an":[113,138],"<inline-formula":[114],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[115],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[116],"<tex-math":[117],"notation=\"LaTeX\">$F1$":[118],"</tex-math></inline-formula>-score":[119],"83.6%,":[121],"exceeding":[122],"performance":[124],"second":[127],"best":[128],"algorithm":[129],"by":[130,149,165],"at":[131],"least":[132],"2%.":[133],"Furthermore,":[134],"demonstrates":[137],"intersection":[139],"over":[140],"union":[141],"(IoU)":[142],"metric":[143],"98.02%,":[145],"surpassing":[146],"competing":[147],"models":[148,176],"a":[150,178],"minimum":[151],"25%.":[153],"This":[154],"research":[155],"highlights":[156],"potential":[158],"scenarios":[163],"characterized":[164],"data":[166],"scarcity":[167],"complex":[169],"processes.":[171],"By":[172],"effectively":[173],"fine-tuning":[174],"large":[175],"with":[177],"small":[179],"amount":[180],"high-quality":[182],"our":[185],"approach":[186],"addresses":[187],"insufficient":[191],"sample":[192],"sizes,":[193],"optimizes":[194],"use":[196],"datasets,":[199],"reduces":[200],"costs,":[202],"significantly":[204],"enhances":[205],"recognition":[206],"accuracy.":[207]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}