{"id":"https://openalex.org/W2965521953","doi":"https://doi.org/10.1109/jstars.2019.2925841","title":"A Novel Deep Structure U-Net for Sea-Land Segmentation in Remote Sensing Images","display_name":"A Novel Deep Structure U-Net for Sea-Land Segmentation in Remote Sensing Images","publication_year":2019,"publication_date":"2019-08-06","ids":{"openalex":"https://openalex.org/W2965521953","doi":"https://doi.org/10.1109/jstars.2019.2925841","mag":"2965521953"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2019.2925841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2019.2925841","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/A_novel_deep_structure_U-Net_for_sea-land_segmentation_in_remote_sensing_images/10208903","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079232252","display_name":"Pourya Shamsolmoali","orcid":"https://orcid.org/0000-0002-0263-1661"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pourya Shamsolmoali","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0263-1661","affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009550171","display_name":"Masoumeh Zareapoor","orcid":"https://orcid.org/0000-0002-3991-0584"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Masoumeh Zareapoor","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3991-0584","affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694558","display_name":"Ruili Wang","orcid":"https://orcid.org/0000-0001-7117-2772"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Ruili Wang","raw_affiliation_strings":["School of Natural and Computational Sciences, Massey University, Palmerston North, New Zealand"],"raw_orcid":"https://orcid.org/0000-0001-7117-2772","affiliations":[{"raw_affiliation_string":"School of Natural and Computational Sciences, Massey University, Palmerston North, New Zealand","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066119228","display_name":"Huiyu Zhou","orcid":"https://orcid.org/0000-0003-1634-9840"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huiyu Zhou","raw_affiliation_strings":["Department of Informatics, University of Leicester, Leicester, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404947","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0003-4801-7162"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4801-7162","affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":10.3344,"has_fulltext":false,"cited_by_count":153,"citation_normalized_percentile":{"value":0.98968402,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"12","issue":"9","first_page":"3219","last_page":"3232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T11698","display_name":"Underwater Acoustics Research","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.991100013256073,"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/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/upsampling","display_name":"Upsampling","score":0.8022679686546326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7598068118095398},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.748120903968811},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5938068628311157},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5565600991249084},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5156925320625305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5155489444732666},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5119339227676392},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.49645596742630005},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43691179156303406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3483978509902954},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3423282206058502},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1580972969532013},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13935551047325134},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1072256863117218},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.077108234167099}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8022679686546326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598068118095398},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.748120903968811},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5938068628311157},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5565600991249084},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5156925320625305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5155489444732666},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5119339227676392},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.49645596742630005},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43691179156303406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3483978509902954},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3423282206058502},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1580972969532013},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13935551047325134},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1072256863117218},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.077108234167099},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jstars.2019.2925841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2019.2925841","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/10208903","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_novel_deep_structure_U-Net_for_sea-land_segmentation_in_remote_sensing_images/10208903","pdf_url":null,"source":{"id":"https://openalex.org/S4306402621","display_name":"INDIGO (University of Illinois at Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39422238","host_organization_name":"University of Illinois Chicago","host_organization_lineage":["https://openalex.org/I39422238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:lra.le.ac.uk:2381/45665","is_oa":true,"landing_page_url":"https://ieeexplore.ieee.org/abstract/document/8789636","pdf_url":null,"source":{"id":"https://openalex.org/S4306402365","display_name":"Leicester Research Archive (University of Leicester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I153648349","host_organization_name":"University of Leicester","host_organization_lineage":["https://openalex.org/I153648349"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/10208903","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_novel_deep_structure_U-Net_for_sea-land_segmentation_in_remote_sensing_images/10208903","pdf_url":null,"source":{"id":"https://openalex.org/S4306402621","display_name":"INDIGO (University of Illinois at Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39422238","host_organization_name":"University of Illinois Chicago","host_organization_lineage":["https://openalex.org/I39422238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G3272709386","display_name":null,"funder_award_id":"61572315 6151101179 2015CB856004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8163518895","display_name":null,"funder_award_id":"EP/N011074/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1973066300","https://openalex.org/W1978271497","https://openalex.org/W2012511141","https://openalex.org/W2017226600","https://openalex.org/W2024251696","https://openalex.org/W2051967942","https://openalex.org/W2054611379","https://openalex.org/W2097117768","https://openalex.org/W2097865154","https://openalex.org/W2106869737","https://openalex.org/W2111975408","https://openalex.org/W2117795858","https://openalex.org/W2118857990","https://openalex.org/W2129817193","https://openalex.org/W2186928867","https://openalex.org/W2194775991","https://openalex.org/W2291529341","https://openalex.org/W2296542445","https://openalex.org/W2302255633","https://openalex.org/W2308607294","https://openalex.org/W2368682324","https://openalex.org/W2423620120","https://openalex.org/W2517954747","https://openalex.org/W2555959783","https://openalex.org/W2556967412","https://openalex.org/W2582996697","https://openalex.org/W2594603277","https://openalex.org/W2616020424","https://openalex.org/W2755576573","https://openalex.org/W2766038477","https://openalex.org/W2767793144","https://openalex.org/W2769197438","https://openalex.org/W2769937543","https://openalex.org/W2774320778","https://openalex.org/W2780544323","https://openalex.org/W2783096881","https://openalex.org/W2788906943","https://openalex.org/W2794948653","https://openalex.org/W2801588621","https://openalex.org/W2803763010","https://openalex.org/W2806895779","https://openalex.org/W2807109687","https://openalex.org/W2807455572","https://openalex.org/W2808611531","https://openalex.org/W2809931234","https://openalex.org/W2884281986","https://openalex.org/W2886397424","https://openalex.org/W2926837263","https://openalex.org/W2949846184","https://openalex.org/W2963446712","https://openalex.org/W2963556638","https://openalex.org/W2963859992","https://openalex.org/W2963881378","https://openalex.org/W2964060597","https://openalex.org/W2964081807","https://openalex.org/W2964121744","https://openalex.org/W2964166828","https://openalex.org/W3099663315","https://openalex.org/W3140517367","https://openalex.org/W4294226146","https://openalex.org/W4301504863","https://openalex.org/W4303859629","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6663484236","https://openalex.org/W6676194229","https://openalex.org/W6698183232","https://openalex.org/W6729983426","https://openalex.org/W6732781371","https://openalex.org/W6740164494","https://openalex.org/W6745672167","https://openalex.org/W6748775820","https://openalex.org/W6840965774"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4385574037","https://openalex.org/W2964954556","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Sea-land":[0],"segmentation":[1,16,180,223],"is":[2,52,84],"an":[3,134],"important":[4],"process":[5],"for":[6,17,44,67],"many":[7],"key":[8],"applications":[9],"in":[10,76,103,142],"remote":[11,18,80],"sensing.":[12],"Proper":[13],"operative":[14],"sea-land":[15,45,69,222],"sensing":[19,81],"images":[20],"remains":[21],"a":[22,61,71,85,161],"challenging":[23],"issue":[24],"due":[25],"to":[26,93,105,117],"complex":[27,77],"and":[28,33,78,90,100,133,145,176,196,198],"diverse":[29],"transition":[30],"between":[31,173],"sea":[32],"land.":[34],"Although":[35],"several":[36,109,204],"convolutional":[37],"neural":[38,64],"networks":[39],"(CNNs)":[40],"have":[41,160,187],"been":[42],"developed":[43],"segmentation,":[46,70],"the":[47,55,106,143,150,154,174,200,216,221],"performance":[48],"of":[49,87,149,164,206],"these":[50],"CNNs":[51],"far":[53],"from":[54,153],"expected":[56],"target.":[57],"This":[58],"paper":[59],"presents":[60],"novel":[62],"deep":[63],"network":[65,113,125,144],"structure":[66],"pixel-wise":[68],"residual":[72,112],"Dense":[73],"U-Net":[74],"(RDU-Net),":[75],"high-density":[79],"images.":[82,156],"RDU-Net":[83,202,214],"combination":[86],"both":[88],"downsampling":[89,99],"upsampling":[91,101],"paths":[92],"achieve":[94],"satisfactory":[95],"results.":[96],"In":[97],"each":[98],"path,":[102],"addition":[104],"convolution":[107,129],"layers,":[108,130],"densely":[110],"connected":[111],"blocks":[114,159],"are":[115,167],"proposed":[116,158,201],"systematically":[118],"aggregate":[119],"multiscale":[120],"contextual":[121],"information.":[122],"Each":[123],"dense":[124,207],"block":[126],"contains":[127],"multilevel":[128],"short-range":[131],"connections,":[132],"identity":[135],"mapping":[136],"connection,":[137],"which":[138],"facilitates":[139],"features":[140,152],"reuse":[141],"makes":[146],"full":[147],"use":[148],"hierarchical":[151],"original":[155],"These":[157],"certain":[162],"number":[163],"connections":[165],"that":[166,213],"designed":[168],"with":[169],"shorter":[170],"distance":[171],"backpropagation":[172],"layers":[175],"can":[177],"significantly":[178],"improve":[179],"results":[181,211],"while":[182],"minimizing":[183],"computational":[184],"costs.":[185],"We":[186],"performed":[188],"extensive":[189],"experiments":[190],"on":[191,220],"two":[192],"real":[193],"datasets,":[194],"Google-Earth":[195],"ISPRS,":[197],"compared":[199],"against":[203],"variations":[205],"networks.":[208],"The":[209],"experimental":[210],"show":[212],"outperforms":[215],"other":[217],"state-of-the-art":[218],"approaches":[219],"tasks.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
