{"id":"https://openalex.org/W4399168725","doi":"https://doi.org/10.1109/tgrs.2024.3407200","title":"A Cross-Domain Object-Semantic Matching Framework for Imbalanced High Spatial Resolution Imagery Water-Body Extraction","display_name":"A Cross-Domain Object-Semantic Matching Framework for Imbalanced High Spatial Resolution Imagery Water-Body Extraction","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399168725","doi":"https://doi.org/10.1109/tgrs.2024.3407200"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3407200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3407200","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5000453270","display_name":"Zhen Li","orcid":"https://orcid.org/0000-0002-6694-7518"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhen Li","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079862010","display_name":"Qiqi Zhu","orcid":"https://orcid.org/0000-0002-5339-0829"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiqi Zhu","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042693325","display_name":"Jiahui Yang","orcid":"https://orcid.org/0000-0003-1021-2894"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]},{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Yang","raw_affiliation_strings":["Tencent Technology (Shenzhen) Co., Ltd., Shenzhen, China","School of Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Tencent Technology (Shenzhen) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"School of Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029437341","display_name":"Jianjun Lv","orcid":"https://orcid.org/0000-0002-8144-1929"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjun Lv","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063647157","display_name":"Qingfeng Guan","orcid":"https://orcid.org/0000-0002-7392-3709"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingfeng Guan","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000453270"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":3.5542,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.92455381,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9541000127792358,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9541000127792358,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9350000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12543","display_name":"Groundwater and Watershed Analysis","score":0.9222999811172485,"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/computer-science","display_name":"Computer science","score":0.7179745435714722},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6193757057189941},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5484304428100586},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5169017314910889},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4958246648311615},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.49011096358299255},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4878092110157013},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4408782720565796},{"id":"https://openalex.org/keywords/water-body","display_name":"Water body","score":0.43488967418670654},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4319620728492737},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4310990273952484},{"id":"https://openalex.org/keywords/image-matching","display_name":"Image matching","score":0.42542850971221924},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4155956506729126},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.25612199306488037},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22971656918525696},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10021325945854187},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06887924671173096}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7179745435714722},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6193757057189941},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5484304428100586},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5169017314910889},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4958246648311615},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.49011096358299255},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4878092110157013},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4408782720565796},{"id":"https://openalex.org/C2986309107","wikidata":"https://www.wikidata.org/wiki/Q15324","display_name":"Water body","level":2,"score":0.43488967418670654},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4319620728492737},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4310990273952484},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.42542850971221924},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4155956506729126},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.25612199306488037},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22971656918525696},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10021325945854187},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06887924671173096},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3407200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3407200","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"awards":[{"id":"https://openalex.org/G8784073608","display_name":null,"funder_award_id":"42271413","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2036841511","https://openalex.org/W2041239487","https://openalex.org/W2061718511","https://openalex.org/W2077509829","https://openalex.org/W2081153373","https://openalex.org/W2101439532","https://openalex.org/W2101678239","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2577554832","https://openalex.org/W2623913549","https://openalex.org/W2630837129","https://openalex.org/W2751181894","https://openalex.org/W2763556461","https://openalex.org/W2781300327","https://openalex.org/W2787091153","https://openalex.org/W2802942478","https://openalex.org/W2804199516","https://openalex.org/W2895281799","https://openalex.org/W2896720583","https://openalex.org/W2924082650","https://openalex.org/W2945318753","https://openalex.org/W2963107255","https://openalex.org/W2963351448","https://openalex.org/W2963881378","https://openalex.org/W2965390952","https://openalex.org/W2969893028","https://openalex.org/W2981512393","https://openalex.org/W2981624307","https://openalex.org/W2987897613","https://openalex.org/W2991488782","https://openalex.org/W3000376294","https://openalex.org/W3005632081","https://openalex.org/W3029999318","https://openalex.org/W3082576756","https://openalex.org/W3101468328","https://openalex.org/W3102977943","https://openalex.org/W3108560336","https://openalex.org/W3111683216","https://openalex.org/W3120804725","https://openalex.org/W3126308856","https://openalex.org/W3135873562","https://openalex.org/W3154061064","https://openalex.org/W3159637683","https://openalex.org/W3195768819","https://openalex.org/W3206476077","https://openalex.org/W3210082318","https://openalex.org/W4205974189","https://openalex.org/W4206571460","https://openalex.org/W4220680175","https://openalex.org/W4281728613","https://openalex.org/W4285807021","https://openalex.org/W4290716516","https://openalex.org/W4303980720","https://openalex.org/W4309194304","https://openalex.org/W4315777148","https://openalex.org/W4324067486","https://openalex.org/W4364322047","https://openalex.org/W4393146401","https://openalex.org/W6675245165","https://openalex.org/W6739696289","https://openalex.org/W6746282794","https://openalex.org/W6767486985","https://openalex.org/W6799579066"],"related_works":["https://openalex.org/W2384918310","https://openalex.org/W2383808867","https://openalex.org/W2372581239","https://openalex.org/W2107893065","https://openalex.org/W2617958085","https://openalex.org/W1509862229","https://openalex.org/W2050706403","https://openalex.org/W1519745258","https://openalex.org/W2193676006","https://openalex.org/W1973922169"],"abstract_inverted_index":{"Large-scale":[0],"information":[1],"pertaining":[2],"to":[3,68,86,148,151,179,192,214],"surface":[4,188],"water":[5,80,119,136,172,189,225],"bodies":[6,81,120,137],"is":[7,82,161,212],"crucial":[8],"for":[9,39,117,143],"activities":[10],"such":[11],"as":[12],"flood":[13],"monitoring.":[14],"Deep":[15],"learning":[16,38],"algorithms":[17],"have":[18],"shown":[19],"great":[20],"potential":[21],"in":[22,55,94,129,204],"water-body":[23,42,103],"extraction":[24,43],"based":[25],"on":[26,36,230],"high":[27],"spatial":[28,56],"resolution":[29,57],"(HSR)":[30],"imagery.":[31,126],"However,":[32],"the":[33,61,69,75,87,100,194,205,216,241],"current":[34],"reliance":[35],"deep":[37,72],"HSR":[40],"imagery":[41],"necessitates":[44],"a":[45,111,155,181,208],"substantial":[46],"quantity":[47],"of":[48,63,71,77,89,102,135,187,218,234,245],"manually":[49],"labeled":[50],"training":[51,195],"samples.":[52],"The":[53,127,163],"variance":[54],"among":[58],"images":[59],"and":[60,132,175,184,221,226,238,243],"intricacies":[62],"scenes":[64],"consistently":[65],"pose":[66],"challenges":[67,142],"transferability":[70],"learning.":[73],"Moreover,":[74],"number":[76,88],"pixels":[78],"representing":[79],"typically":[83],"lower":[84],"compared":[85],"background":[90],"pixels.":[91],"This":[92],"imbalance":[93,217],"class":[95,104],"prediction":[96],"probabilities":[97,220],"often":[98],"limits":[99],"accuracy":[101],"predictions.":[105],"In":[106],"this":[107],"paper,":[108],"we":[109],"propose":[110],"cross-domain":[112],"object-semantic":[113],"matching":[114,159],"(COM)":[115],"framework":[116],"extracting":[118],"from":[121,197],"unlabeled":[122],"high-resolution":[123],"remote":[124],"sensing":[125],"distinctions":[128],"spectra,":[130],"shapes,":[131],"semantic":[133,157],"distributions":[134],"across":[138],"various":[139],"domains":[140],"create":[141],"certain":[144],"source":[145],"domain":[146],"samples":[147],"contribute":[149],"positively":[150],"model":[152],"training.":[153],"Therefore,":[154],"sample":[156],"similarity":[158],"mechanism":[160],"devised.":[162],"proposed":[164,247],"object":[165],"contextual":[166],"perception":[167],"network":[168],"(OCPNet)":[169],"models":[170],"multi-scale":[171],"body":[173],"features":[174],"object-contextual":[176],"representations,":[177],"aiming":[178],"achieve":[180],"more":[182],"accurate":[183],"comprehensive":[185],"representation":[186],"bodies.":[190,228],"Additionally,":[191],"prevent":[193],"process":[196],"being":[198],"dominated":[199],"by":[200],"easily":[201],"transferred":[202],"categories":[203],"target":[206],"domain,":[207],"weighted":[209],"joint":[210],"loss":[211],"designed":[213],"alleviate":[215],"predicted":[219],"pixel":[222],"numbers":[223],"between":[224],"non-water":[227],"Experiments":[229],"four":[231],"public":[232],"datasets":[233],"GID,":[235],"CCF,":[236],"LoveDA":[237],"DeepGlobe":[239],"demonstrate":[240],"effectiveness":[242],"generalization":[244],"our":[246],"framework.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}