{"id":"https://openalex.org/W4396855325","doi":"https://doi.org/10.3390/rs16101725","title":"ABNet: An Aggregated Backbone Network Architecture for Fine Landcover Classification","display_name":"ABNet: An Aggregated Backbone Network Architecture for Fine Landcover Classification","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4396855325","doi":"https://doi.org/10.3390/rs16101725"},"language":"en","primary_location":{"id":"doi:10.3390/rs16101725","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16101725","pdf_url":"https://www.mdpi.com/2072-4292/16/10/1725/pdf?version=1715608722","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/10/1725/pdf?version=1715608722","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111194538","display_name":"Bo Si","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Si","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101874415","display_name":"Zhennan Wang","orcid":"https://orcid.org/0000-0002-5814-3798"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhennan Wang","raw_affiliation_strings":["Zhejiang Shuzhi Space Planning and Design Co., Ltd., Hangzhou 310030, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Shuzhi Space Planning and Design Co., Ltd., Hangzhou 310030, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074346212","display_name":"Zhoulu Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhoulu Yu","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100628775","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0002-0797-4655"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Wang","raw_affiliation_strings":["College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5074346212"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.2044,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43297981,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"16","issue":"10","first_page":"1725","last_page":"1725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5952037572860718},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.47482356429100037},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.35197946429252625},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21812644600868225},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1537466049194336}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5952037572860718},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.47482356429100037},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35197946429252625},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21812644600868225},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1537466049194336},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16101725","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16101725","pdf_url":"https://www.mdpi.com/2072-4292/16/10/1725/pdf?version=1715608722","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:510a1a6b92bd4ffbb39e3f311c71de68","is_oa":true,"landing_page_url":"https://doaj.org/article/510a1a6b92bd4ffbb39e3f311c71de68","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":"Remote Sensing, Vol 16, Iss 10, p 1725 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16101725","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16101725","pdf_url":"https://www.mdpi.com/2072-4292/16/10/1725/pdf?version=1715608722","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.6600000262260437,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396855325.pdf"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2480078828","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2884585870","https://openalex.org/W2884822772","https://openalex.org/W2890554434","https://openalex.org/W2913160016","https://openalex.org/W2916798096","https://openalex.org/W2928165649","https://openalex.org/W2940726923","https://openalex.org/W2946948417","https://openalex.org/W2955058313","https://openalex.org/W2961699889","https://openalex.org/W2963446712","https://openalex.org/W2964309882","https://openalex.org/W2970987838","https://openalex.org/W2991488782","https://openalex.org/W2997050303","https://openalex.org/W2998228095","https://openalex.org/W3004265084","https://openalex.org/W3033496625","https://openalex.org/W3040304705","https://openalex.org/W3050436783","https://openalex.org/W3080358119","https://openalex.org/W3097823855","https://openalex.org/W3129544296","https://openalex.org/W3137154434","https://openalex.org/W3166398490","https://openalex.org/W3174470190","https://openalex.org/W3174765561","https://openalex.org/W3176270344","https://openalex.org/W3199523484","https://openalex.org/W3205350007","https://openalex.org/W4200628355","https://openalex.org/W4210670727","https://openalex.org/W4281651885","https://openalex.org/W4289944387","https://openalex.org/W4293660728","https://openalex.org/W4295532986","https://openalex.org/W4306771920","https://openalex.org/W4307494192","https://openalex.org/W4312330766","https://openalex.org/W4313472245","https://openalex.org/W4313908836","https://openalex.org/W4315777148","https://openalex.org/W4367325736","https://openalex.org/W4384557959","https://openalex.org/W4386175477","https://openalex.org/W4387019919","https://openalex.org/W4389069581"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"High-precision":[0],"landcover":[1,45,60,134],"classification":[2,61,72,102,107],"is":[3],"a":[4,75,87,119,152,255],"fundamental":[5],"prerequisite":[6],"for":[7,100,131],"resource":[8],"and":[9,12,21,84,109,144,193,217,249,275,289],"environmental":[10],"monitoring":[11],"land-use":[13],"status":[14],"surveys.":[15],"Imbued":[16],"with":[17,161,254],"intricate":[18],"spatial":[19,26,190],"information":[20,220],"texture":[22],"features,":[23],"very":[24],"high":[25],"resolution":[27],"remote":[28],"sensing":[29],"images":[30],"accentuate":[31],"the":[32,37,42,71,91,106,111,126,132,162,167,182,188,222,237,247,283,287,294],"divergence":[33],"between":[34],"features":[35,179],"within":[36,221],"same":[38],"category,":[39],"thereby":[40,198],"amplifying":[41],"complexity":[43],"of":[44,74,95,113,231,243,293],"classification.":[46,135],"Consequently,":[47],"semantic":[48,114,121,202],"segmentation":[49,115,122,280],"models":[50,268],"leveraging":[51],"deep":[52],"backbone":[53,77,98,128,140,184,257],"networks":[54,141,160],"have":[55],"emerged":[56],"as":[57],"stalwarts":[58],"in":[59,67,90,236,261],"tasks":[62],"owing":[63],"to":[64,263],"their":[65],"adeptness":[66],"feature":[68,203,224],"representation.":[69],"However,":[70],"efficacy":[73],"solitary":[76],"network":[78,99,123,129,258],"model":[79],"fluctuates":[80],"across":[81,205,282],"diverse":[82],"scenarios":[83],"datasets,":[85,285],"posing":[86],"persistent":[88],"challenge":[89],"construction":[92],"or":[93,266],"selection":[94],"an":[96,229],"appropriate":[97],"distinct":[101,177],"tasks.":[103],"To":[104],"elevate":[105],"performance":[108,281],"bolster":[110],"generalization":[112,291],"models,":[116],"we":[117],"propose":[118],"novel":[120],"architecture,":[124],"named":[125],"aggregated":[127,223],"(ABNet),":[130],"meticulous":[133],"ABNet":[136,244,277],"aggregates":[137],"three":[138,183],"prevailing":[139],"(ResNet,":[142],"HRNet,":[143],"VoVNet),":[145],"distinguished":[146],"by":[147,181],"significant":[148],"structural":[149],"disparities,":[150],"using":[151],"same-stage":[153],"fusion":[154],"approach.":[155,296],"Subsequently,":[156],"it":[157],"amalgamates":[158],"these":[159],"Deeplabv3+":[163],"head":[164],"after":[165],"integrating":[166],"convolutional":[168,209],"block":[169,210],"attention":[170,211],"mechanism":[171,212],"(CBAM).":[172],"Notably,":[173],"this":[174],"amalgamation":[175],"harmonizes":[176],"scale":[178],"extracted":[180],"networks,":[185],"thus":[186],"enriching":[187],"model\u2019s":[189],"contextual":[191],"comprehension":[192],"expanding":[194],"its":[195],"receptive":[196],"field,":[197],"facilitating":[199],"more":[200],"effective":[201],"extraction":[204],"different":[206],"stages.":[207],"The":[208],"primarily":[213],"orchestrates":[214],"channel":[215],"adjustments":[216],"curtails":[218],"redundant":[219],"layers.":[225],"Ablation":[226],"experiments":[227],"demonstrate":[228],"enhancement":[230],"no":[232],"less":[233],"than":[234],"3%":[235],"mean":[238],"intersection":[239],"over":[240],"union":[241],"(mIoU)":[242],"on":[245],"both":[246],"LoveDA":[248],"GID15":[250],"datasets":[251],"when":[252],"compared":[253],"single":[256],"model.":[259],"Furthermore,":[260],"contrast":[262],"seven":[264],"classical":[265],"state-of-the-art":[267],"(UNet,":[269],"FPN,":[270],"PSPNet,":[271],"DANet,":[272],"CBNet,":[273],"CCNet,":[274],"UPerNet),":[276],"evinces":[278],"excellent":[279],"aforementioned":[284],"underscoring":[286],"efficiency":[288],"robust":[290],"capabilities":[292],"proposed":[295]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}