{"id":"https://openalex.org/W4414908537","doi":"https://doi.org/10.1109/access.2025.3618967","title":"Classification of Broad-Leaved Forest Tree Species Based on HSFC-DeepLabV3+ in UAV Multispectral Images","display_name":"Classification of Broad-Leaved Forest Tree Species Based on HSFC-DeepLabV3+ in UAV Multispectral Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414908537","doi":"https://doi.org/10.1109/access.2025.3618967"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3618967","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3618967","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.2025.3618967","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106033870","display_name":"Xiaole Liu","orcid":"https://orcid.org/0009-0006-3605-8206"},"institutions":[{"id":"https://openalex.org/I4210119087","display_name":"North China Institute of Aerospace Engineering","ror":"https://ror.org/02m7msy24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaole Liu","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China","institution_ids":["https://openalex.org/I4210119087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053202958","display_name":"Linghan Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119087","display_name":"North China Institute of Aerospace Engineering","ror":"https://ror.org/02m7msy24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linghan Gao","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China"],"raw_orcid":"https://orcid.org/0009-0009-5834-0220","affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China","institution_ids":["https://openalex.org/I4210119087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100537267","display_name":"Jia Cui","orcid":"https://orcid.org/0000-0002-7118-0198"},"institutions":[{"id":"https://openalex.org/I4210119087","display_name":"North China Institute of Aerospace Engineering","ror":"https://ror.org/02m7msy24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cui Jia","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China","institution_ids":["https://openalex.org/I4210119087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101739055","display_name":"Yihao Cai","orcid":"https://orcid.org/0009-0005-6325-2605"},"institutions":[{"id":"https://openalex.org/I4210119087","display_name":"North China Institute of Aerospace Engineering","ror":"https://ror.org/02m7msy24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yushun Cai","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China","institution_ids":["https://openalex.org/I4210119087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018649852","display_name":"Guanxing Wang","orcid":"https://orcid.org/0000-0003-1447-0962"},"institutions":[{"id":"https://openalex.org/I4210119087","display_name":"North China Institute of Aerospace Engineering","ror":"https://ror.org/02m7msy24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanxing Wang","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China","institution_ids":["https://openalex.org/I4210119087"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ying Tian","orcid":"https://orcid.org/0009-0000-8090-762X"},"institutions":[{"id":"https://openalex.org/I4210119087","display_name":"North China Institute of Aerospace Engineering","ror":"https://ror.org/02m7msy24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Tian","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China"],"raw_orcid":"https://orcid.org/0009-0000-8090-762X","affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang, China","institution_ids":["https://openalex.org/I4210119087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210119087"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28477901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"174517","last_page":"174534"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9631999731063843,"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":0.9574999809265137,"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/multispectral-image","display_name":"Multispectral image","score":0.7091000080108643},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5324000120162964},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5169000029563904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5081999897956848},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.46540001034736633},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43549999594688416},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.41110000014305115},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4097999930381775},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.40230000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7878000140190125},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7091000080108643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5845999717712402},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5324000120162964},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5081999897956848},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4392000138759613},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43549999594688416},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.41110000014305115},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.40230000019073486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3783000111579895},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3743000030517578},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.35519999265670776},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.273499995470047},{"id":"https://openalex.org/C56289965","wikidata":"https://www.wikidata.org/wiki/Q5249246","display_name":"Decision tree model","level":3,"score":0.25099998712539673},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3618967","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3618967","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:cdd1536fad5c4e5b9134a8cb91d326de","is_oa":true,"landing_page_url":"https://doaj.org/article/cdd1536fad5c4e5b9134a8cb91d326de","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 174517-174534 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3618967","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3618967","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":[],"awards":[{"id":"https://openalex.org/G6193852842","display_name":null,"funder_award_id":"D2025409010","funder_id":"https://openalex.org/F4320336623","funder_display_name":"Sichuan Education and Scientific Research Grant Project"}],"funders":[{"id":"https://openalex.org/F4320336623","display_name":"Sichuan Education and Scientific Research Grant Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1990653740","https://openalex.org/W1993766631","https://openalex.org/W2035549557","https://openalex.org/W2046788667","https://openalex.org/W2412782625","https://openalex.org/W2482693827","https://openalex.org/W2515306179","https://openalex.org/W2787091153","https://openalex.org/W2843415492","https://openalex.org/W3015716208","https://openalex.org/W3043740003","https://openalex.org/W3120119699","https://openalex.org/W3129659759","https://openalex.org/W3134978274","https://openalex.org/W3137032663","https://openalex.org/W3177223813","https://openalex.org/W4280533938","https://openalex.org/W4309690975","https://openalex.org/W4367181824","https://openalex.org/W4367397178","https://openalex.org/W4382598168","https://openalex.org/W4384406330","https://openalex.org/W4387909279","https://openalex.org/W4389390400","https://openalex.org/W4389792990","https://openalex.org/W4395703452","https://openalex.org/W4396927685","https://openalex.org/W4399269537","https://openalex.org/W4404960291"],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"focuses":[2],"on":[3],"the":[4,13,26,58,137],"automatic":[5],"classification":[6,45,90,204],"of":[7,16,28,134,139,145],"broad-leaved":[8],"forest":[9],"tree":[10],"species":[11],"in":[12,147,152,159,205],"Millennium":[14],"Forest":[15],"Xiongan":[17],"New":[18],"Area":[19],"using":[20],"UAV-based":[21],"multispectral":[22],"imagery.":[23],"To":[24],"address":[25],"limitations":[27],"existing":[29],"semantic":[30,75],"segmentation":[31],"models":[32,128],"such":[33],"as":[34,57,195],"DeepLabV3+,":[35],"we":[36],"propose":[37],"HSFC-DeepLabV3+,":[38],"an":[39,78],"enhanced":[40],"model":[41,50,117,142,185],"that":[42],"significantly":[43],"improves":[44],"accuracy":[46,149,155],"and":[47,86,95,111,124,132,157,169,175],"efficiency.":[48],"The":[49,141],"introduces":[51],"four":[52],"key":[53],"enhancements:":[54],"(1)":[55],"EnhancedMobileNetV2":[56],"backbone":[59],"with":[60,92,126,182],"SEBlock":[61],"integration":[62],"for":[63,81,199],"improved":[64],"feature":[65,84],"extraction;":[66],"(2)":[67],"SeparableASPP":[68],"to":[69,97,115,180],"reduce":[70],"computational":[71],"complexity":[72],"while":[73,163],"preserving":[74],"context;":[76],"(3)":[77],"FPNFusion":[79],"module":[80],"effective":[82],"multi-scale":[83],"fusion;":[85],"(4)":[87],"a":[88,101,196],"deeper":[89],"head":[91],"multi-layer":[93],"convolutions":[94],"Dropout":[96],"boost":[98],"generalization.":[99],"Additionally,":[100],"hybrid":[102],"data":[103],"augmentation":[104],"strategy":[105],"combining":[106],"bilinear":[107],"interpolation,":[108],"geometric":[109],"transformation,":[110],"Mixup":[112],"is":[113],"employed":[114],"enhance":[116],"robustness.":[118],"Extensive":[119],"experiments,":[120],"including":[121],"ablation":[122],"studies":[123],"comparisons":[125],"state-of-the-art":[127],"(e.g.,":[129],"HRNet,":[130],"PSPNet,":[131],"variants":[133],"DeepLabV3+),":[135],"demonstrate":[136],"superiority":[138],"HSFC-DeepLabV3+.":[140],"achieves":[143],"improvements":[144],"2.55%":[146],"overall":[148],"(OA),":[150],"4.72%":[151],"mean":[153,160],"pixel":[154],"(MPA),":[156],"9.32%":[158],"IoU":[161],"(mIoU),":[162],"reducing":[164],"total":[165],"loss,":[166,168],"validation":[167],"training":[170],"time":[171],"by":[172],"0.065%,":[173],"0.076%,":[174],"27.58":[176],"hours,":[177],"respectively.":[178],"Compared":[179],"DeepLabV3+":[181],"MobileNetV2,":[183],"our":[184],"also":[186],"shows":[187],"notable":[188],"performance":[189],"gains.":[190],"These":[191],"results":[192],"highlight":[193],"HSFC-DeepLabV3+":[194],"promising":[197],"tool":[198],"high-precision,":[200],"efficient":[201],"remote":[202],"sensing":[203],"forestry":[206],"applications.":[207]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}