{"id":"https://openalex.org/W4205974189","doi":"https://doi.org/10.3390/rs14010206","title":"Multi-Scale Feature Aggregation Network for Water Area Segmentation","display_name":"Multi-Scale Feature Aggregation Network for Water Area Segmentation","publication_year":2022,"publication_date":"2022-01-03","ids":{"openalex":"https://openalex.org/W4205974189","doi":"https://doi.org/10.3390/rs14010206"},"language":"en","primary_location":{"id":"doi:10.3390/rs14010206","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14010206","pdf_url":"https://www.mdpi.com/2072-4292/14/1/206/pdf?version=1641282521","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/2072-4292/14/1/206/pdf?version=1641282521","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048675276","display_name":"Kai Hu","orcid":"https://orcid.org/0000-0001-7181-9935"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Hu","raw_affiliation_strings":["Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, B-DAT, Nanjing University of Information Science and Technology, Nanjing 210044, China"],"raw_orcid":"https://orcid.org/0000-0001-7181-9935","affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, B-DAT, Nanjing University of Information Science and Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071684102","display_name":"Meng Li","orcid":"https://orcid.org/0000-0002-3156-9836"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Li","raw_affiliation_strings":["Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, B-DAT, Nanjing University of Information Science and Technology, Nanjing 210044, China"],"raw_orcid":"https://orcid.org/0000-0002-3156-9836","affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, B-DAT, Nanjing University of Information Science and Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045380530","display_name":"Min Xia","orcid":"https://orcid.org/0000-0003-4681-9129"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Xia","raw_affiliation_strings":["Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, B-DAT, Nanjing University of Information Science and Technology, Nanjing 210044, China"],"raw_orcid":"https://orcid.org/0000-0003-4681-9129","affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, B-DAT, Nanjing University of Information Science and Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058852174","display_name":"Haifeng Lin","orcid":"https://orcid.org/0000-0002-3835-6075"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Lin","raw_affiliation_strings":["College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China","institution_ids":["https://openalex.org/I167027274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045380530"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.9327,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.96414972,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"14","issue":"1","first_page":"206","last_page":"206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9882000088691711,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9882000088691711,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9746999740600586,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9742000102996826,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8169583082199097},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.7537310123443604},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6901593208312988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6709534525871277},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5870396494865417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5509332418441772},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45272305607795715},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.450493723154068},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.42681893706321716},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4187008738517761},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41041356325149536},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4032345414161682},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36660125851631165},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08006083965301514},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07977268099784851},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0785737931728363}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8169583082199097},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.7537310123443604},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6901593208312988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6709534525871277},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5870396494865417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5509332418441772},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45272305607795715},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.450493723154068},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.42681893706321716},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4187008738517761},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41041356325149536},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4032345414161682},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36660125851631165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08006083965301514},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07977268099784851},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0785737931728363},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14010206","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14010206","pdf_url":"https://www.mdpi.com/2072-4292/14/1/206/pdf?version=1641282521","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:96db212dcf074294822e160814226b01","is_oa":true,"landing_page_url":"https://doaj.org/article/96db212dcf074294822e160814226b01","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 14, Iss 1, p 206 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/1/206/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14010206","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing; Volume 14; Issue 1; Pages: 206","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14010206","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14010206","pdf_url":"https://www.mdpi.com/2072-4292/14/1/206/pdf?version=1641282521","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":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"awards":[{"id":"https://openalex.org/G7717822188","display_name":null,"funder_award_id":"42075130","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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205974189.pdf"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W119228284","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1975910143","https://openalex.org/W2040568291","https://openalex.org/W2066734832","https://openalex.org/W2077509829","https://openalex.org/W2084598622","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2135996564","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2529154790","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2604844733","https://openalex.org/W2752782242","https://openalex.org/W2799166040","https://openalex.org/W2799213142","https://openalex.org/W2884585870","https://openalex.org/W2886934227","https://openalex.org/W2922509574","https://openalex.org/W2963125010","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2981413347","https://openalex.org/W3003442407","https://openalex.org/W3016664505","https://openalex.org/W3022378226","https://openalex.org/W3037815104","https://openalex.org/W3047725879","https://openalex.org/W3081260473","https://openalex.org/W3138896524","https://openalex.org/W3160032272","https://openalex.org/W3163489199","https://openalex.org/W3176270344","https://openalex.org/W3189133113","https://openalex.org/W3198879287","https://openalex.org/W3200526086","https://openalex.org/W3204937691","https://openalex.org/W3209239396","https://openalex.org/W3209695792","https://openalex.org/W6803420298"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W4249847449","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W44395729","https://openalex.org/W4390494008"],"abstract_inverted_index":{"Water":[0],"area":[1,17,224],"segmentation":[2,47,201],"is":[3,48,116,159,206],"an":[4],"important":[5,217],"branch":[6],"of":[7,39,46,68,99,106,129,152,174,188,199],"remote":[8],"sensing":[9],"image":[10,190],"segmentation,":[11],"but":[12],"in":[13,138,203,210],"reality,":[14],"most":[15],"water":[16,223],"images":[18],"have":[19],"complex":[20],"and":[21,36,42,95,104,108,155,178,215],"diverse":[22],"backgrounds.":[23],"Traditional":[24],"detection":[25,213],"methods":[26],"cannot":[27],"accurately":[28],"identify":[29],"small":[30],"tributaries":[31],"due":[32],"to":[33,64,71,86,118,124,146,170,183],"incomplete":[34],"mining":[35],"insufficient":[37],"utilization":[38],"semantic":[40,102,150],"information,":[41,74],"the":[43,52,66,69,91,112,126,130,133,139,149,153,156,162,167,172,175,185,197,200,211,221],"edge":[44],"information":[45,103,128,151,158,164],"rough.":[49],"To":[50],"solve":[51],"above":[53],"problems,":[54],"we":[55,75],"propose":[56],"a":[57,77,83],"multi-scale":[58,84,100],"feature":[59,79],"aggregation":[60,114],"network.":[61,176],"In":[62],"order":[63],"improve":[65,171],"ability":[67,173],"network":[70],"process":[72],"boundary":[73],"design":[76],"deep":[78,101,157],"extraction":[80,98],"module":[81,115,143,169],"using":[82],"pyramid":[85],"extract":[87,148],"features,":[88],"combined":[89],"with":[90,120,161],"designed":[92,137],"attention":[93],"mechanism":[94],"strip":[96],"convolution,":[97],"enhancement":[105],"spatial":[107],"location":[109,186],"information.":[110],"Then,":[111],"multi-branch":[113,168],"used":[117,145,182],"interact":[119],"different":[121],"scale":[122],"features":[123,180],"enhance":[125],"positioning":[127],"pixels.":[131],"Finally,":[132],"two":[134],"high-performance":[135],"branches":[136],"Feature":[140],"Fusion":[141],"Upsample":[142],"are":[144,181],"deeply":[147],"image,":[154],"fused":[160],"shallow":[163],"generated":[165],"by":[166],"Global":[177],"local":[179],"determine":[184],"distribution":[187],"each":[189],"category.":[191],"The":[192],"experimental":[193],"results":[194],"show":[195],"that":[196,209],"accuracy":[198],"method":[202],"this":[204],"paper":[205],"better":[207],"than":[208],"previous":[212],"methods,":[214],"has":[216],"practical":[218],"significance":[219],"for":[220],"actual":[222],"segmentation.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":7}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2022-01-25T00:00:00"}