{"id":"https://openalex.org/W4402822926","doi":"https://doi.org/10.1109/access.2024.3467998","title":"A Fusion Method Incorporating Dual-Attention Mechanism and Transfer Learning Into UNet++ for Remote Sensing Image Coastline Extraction","display_name":"A Fusion Method Incorporating Dual-Attention Mechanism and Transfer Learning Into UNet++ for Remote Sensing Image Coastline Extraction","publication_year":2024,"publication_date":"2024-09-25","ids":{"openalex":"https://openalex.org/W4402822926","doi":"https://doi.org/10.1109/access.2024.3467998"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3467998","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3467998","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":null,"license_id":null,"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.2024.3467998","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006076158","display_name":"Yanru Song","orcid":"https://orcid.org/0009-0004-8105-244X"},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanru Song","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China","institution_ids":["https://openalex.org/I2799486974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077287636","display_name":"Xue Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092591","display_name":"China Centre for Resources Satellite Data and Application","ror":"https://ror.org/00ft0fw96","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092591"]},{"id":"https://openalex.org/I4210120093","display_name":"Remote Sensing Application Center","ror":"https://ror.org/029rkt035","country_code":"BG","type":"facility","lineage":["https://openalex.org/I4210120093"]}],"countries":["BG","CN"],"is_corresponding":false,"raw_author_name":"Bai Xue","raw_affiliation_strings":["MNR Land Satellite Remote Sensing Application Center, Beijing, China","Land Satellite Remote Sensing Application Center, MNR, Beijing, China"],"affiliations":[{"raw_affiliation_string":"MNR Land Satellite Remote Sensing Application Center, Beijing, China","institution_ids":["https://openalex.org/I4210120093","https://openalex.org/I4210092591"]},{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, MNR, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113400596","display_name":"Yueyue Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueyue Meng","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China","institution_ids":["https://openalex.org/I2799486974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079036062","display_name":"Qin Xiang","orcid":"https://orcid.org/0000-0001-6603-6872"},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Qin","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China","institution_ids":["https://openalex.org/I2799486974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101754633","display_name":"Yixiao Li","orcid":"https://orcid.org/0000-0001-8895-3663"},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiao Li","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China","institution_ids":["https://openalex.org/I2799486974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114233506","display_name":"Qi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing, China","institution_ids":["https://openalex.org/I2799486974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5006076158"],"corresponding_institution_ids":["https://openalex.org/I2799486974"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.599,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85767015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"11320","last_page":"11331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9556000232696533,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9390000104904175,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.729788064956665},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5541307330131531},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5457273721694946},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5167783498764038},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5042001008987427},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4994933605194092},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4930107295513153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4773530960083008},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.43955421447753906},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4129319190979004},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3280937075614929},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16800141334533691}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.729788064956665},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5541307330131531},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5457273721694946},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5167783498764038},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5042001008987427},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4994933605194092},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4930107295513153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4773530960083008},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.43955421447753906},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4129319190979004},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3280937075614929},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16800141334533691},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3467998","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3467998","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1ac845edbd3e44fb8e5d5b3c751e9347","is_oa":true,"landing_page_url":"https://doaj.org/article/1ac845edbd3e44fb8e5d5b3c751e9347","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":"IEEE Access, Vol 13, Pp 11320-11331 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3467998","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3467998","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1958291604","https://openalex.org/W2077509829","https://openalex.org/W2089542421","https://openalex.org/W2112796928","https://openalex.org/W2133059825","https://openalex.org/W2141200610","https://openalex.org/W2198724430","https://openalex.org/W2351028376","https://openalex.org/W2356595539","https://openalex.org/W2364987829","https://openalex.org/W2381966470","https://openalex.org/W2546523301","https://openalex.org/W2774320778","https://openalex.org/W2789914625","https://openalex.org/W2890554472","https://openalex.org/W2963859992","https://openalex.org/W2999563477","https://openalex.org/W3042286316","https://openalex.org/W3102619772","https://openalex.org/W3139912591","https://openalex.org/W4383570504","https://openalex.org/W4387819679","https://openalex.org/W4392192268","https://openalex.org/W6618372016","https://openalex.org/W6638042130","https://openalex.org/W6755521448","https://openalex.org/W6770066768","https://openalex.org/W6773839719"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W2515288625","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3214791684","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2095903272"],"abstract_inverted_index":{"The":[0],"segmentation":[1,59,74,170,196,238],"of":[2,11,48,72,112,119,139,152,209,218,247],"land":[3],"and":[4,17,23,30,45,81,154,183,193,203,234,251],"sea":[5],"in":[6,58,75,230,262],"remote":[7,51,78,212],"sensing":[8,52,79,213],"imagery":[9],"is":[10,101,128,145],"great":[12],"significance":[13],"for":[14,168,198,223],"coastline":[15,21,113,169,224],"extraction":[16,24,225,246],"dynamic":[18],"monitoring.":[19],"Traditional":[20],"recognition":[22],"methods":[25],"based":[26],"on":[27],"spectral":[28,252],"features":[29,114,151,253],"image":[31,37,214],"processing":[32],"can":[33],"only":[34],"generate":[35],"limited":[36],"feature":[38],"results":[39,163,197],"when":[40],"facing":[41],"the":[42,70,84,91,104,109,117,137,149,156,165,175,185,207,216,219],"complex":[43],"textures":[44],"spatial":[46,248],"distributions":[47],"high-spatial":[49,76,210],"resolution":[50,77,211],"images,":[53,256],"leading":[54],"to":[55,69,89,94,107,130,147,159,174,259],"low":[56],"accuracy":[57,138],"outcomes.":[60],"This":[61,240],"paper":[62],"applies":[63],"a":[64,97,243],"deep":[65],"convolutional":[66],"neural":[67],"network":[68,106,188],"problem":[71],"sea-land":[73],"images":[80],"innovates":[82],"upon":[83],"classic":[85],"encoder-decoder":[86],"architecture.":[87],"Firstly,":[88],"enhance":[90,131,155],"network\u2019s":[92,157],"ability":[93,158],"distinguish":[95],"coastlines,":[96,199],"dual":[98],"attention":[99],"mechanism":[100],"introduced":[102],"into":[103],"UNet++":[105,187,221],"improve":[108],"learning":[110,118,144],"capacity":[111],"while":[115],"suppressing":[116],"non-coastline":[120],"features.":[121],"Secondly,":[122],"an":[123,260],"improved":[124,186],"joint":[125],"loss":[126],"function":[127],"adopted":[129],"training":[132],"effectiveness,":[133],"thereby":[134],"significantly":[135],"improving":[136],"semantic":[140,237],"segmentation.":[141],"Lastly,":[142],"transfer":[143],"utilized":[146],"strengthen":[148],"detailed":[150],"coastlines":[153],"identify":[160],"them.":[161],"Experimental":[162],"using":[164],"GID":[166],"dataset":[167],"demonstrate":[171],"that":[172],"compared":[173],"latest":[176],"algorithms":[177],"such":[178],"as":[179],"PSPNet,":[180],"CS-Deeplab":[181],"v3+,":[182],"UNet++,":[184],"achieves":[189],"lower":[190],"boundary":[191,232],"blurriness":[192],"more":[194,244],"accurate":[195],"with":[200],"fewer":[201],"missed":[202],"false":[204],"detections.":[205],"Amidst":[206],"proliferation":[208],"data,":[215],"utilization":[217],"enhanced":[220],"model":[222],"has":[226],"demonstrated":[227],"remarkable":[228],"abilities":[229],"preserving":[231],"information":[233],"achieving":[235],"superior":[236],"performance.":[239],"advancement":[241],"enables":[242],"refined":[245],"distributions,":[249],"textures,":[250],"from":[254],"these":[255],"ultimately":[257],"contributing":[258],"improvement":[261],"classification":[263],"accuracy.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
