{"id":"https://openalex.org/W4407900561","doi":"https://doi.org/10.1109/tgrs.2025.3544549","title":"Deep Merge: Deep-Learning-Based Region Merging for Remote Sensing Image Segmentation","display_name":"Deep Merge: Deep-Learning-Based Region Merging for Remote Sensing Image Segmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407900561","doi":"https://doi.org/10.1109/tgrs.2025.3544549"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3544549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3544549","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":true,"oa_status":"green","oa_url":"https://research.utwente.nl/en/publications/73b94e47-af6d-4220-b496-b475c82ecbec","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026947952","display_name":"Xianwei Lv","orcid":"https://orcid.org/0000-0002-1574-8500"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianwei Lv","raw_affiliation_strings":["School of Computer and Communication Engineering, Hebei Key Laboratory of Marine Perception Network and Data Processing, Northeastern University at Qinhuangdao, Qinhuangdao, China","School of Computer and Communication Engineering, Hebei Key Laboratory of Marine Perception Network and Data Processing, Northeastern University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-1574-8500","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Hebei Key Laboratory of Marine Perception Network and Data Processing, Northeastern University at Qinhuangdao, Qinhuangdao, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"School of Computer and Communication Engineering, Hebei Key Laboratory of Marine Perception Network and Data Processing, Northeastern University, Qinhuangdao, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029035818","display_name":"Claudio Persello","orcid":"https://orcid.org/0000-0003-3742-5398"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Claudio Persello","raw_affiliation_strings":["ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands","ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-3742-5398","affiliations":[{"raw_affiliation_string":"ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]},{"raw_affiliation_string":"ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044816349","display_name":"Wangbin Li","orcid":"https://orcid.org/0000-0003-1841-4247"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangbin Li","raw_affiliation_strings":["State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","School of Computer and Communication Engineering, Hebei Key Laboratory of Marine Perception Network and Data Processing, Northeastern University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0003-1841-4247","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer and Communication Engineering, Hebei Key Laboratory of Marine Perception Network and Data Processing, Northeastern University, Qinhuangdao, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060706069","display_name":"Xiao Huang","orcid":"https://orcid.org/0000-0002-4323-382X"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Huang","raw_affiliation_strings":["Department of Environmental Sciences, Emory University, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4323-382X","affiliations":[{"raw_affiliation_string":"Department of Environmental Sciences, Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025493288","display_name":"Dongping Ming","orcid":"https://orcid.org/0000-0002-3422-7399"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]},{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Dongping Ming","raw_affiliation_strings":["School of Information Engineering, China University of Geosciences (Beijing), Beijing, China","Department of Environmental Sciences, Emory University, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3422-7399","affiliations":[{"raw_affiliation_string":"School of Information Engineering, China University of Geosciences (Beijing), Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"Department of Environmental Sciences, Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082935691","display_name":"Alfred Stein","orcid":"https://orcid.org/0000-0002-9456-1233"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Alfred Stein","raw_affiliation_strings":["ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands","ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-9456-1233","affiliations":[{"raw_affiliation_string":"ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]},{"raw_affiliation_string":"ITC Faculty Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands","institution_ids":["https://openalex.org/I94624287"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.3337,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.95476366,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9707000255584717,"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":0.9707000255584717,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9706000089645386,"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":0.9699000120162964,"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/image-segmentation","display_name":"Image segmentation","score":0.6423417329788208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6366097331047058},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6218602657318115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6193930506706238},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5489332675933838},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5274173021316528},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.5037016272544861},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3869157135486603},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38331031799316406},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.28446459770202637}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6423417329788208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6366097331047058},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6218602657318115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6193930506706238},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5489332675933838},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5274173021316528},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.5037016272544861},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3869157135486603},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38331031799316406},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.28446459770202637},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2025.3544549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3544549","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"},{"id":"pmh:oai:ris.utwente.nl:openaire/73b94e47-af6d-4220-b496-b475c82ecbec","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/73b94e47-af6d-4220-b496-b475c82ecbec","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lv, X, Persello, C, Li, W, Huang, X, Ming, D & Stein, A 2025, 'Deep Merge : Deep-Learning-Based Region Merging for Remote Sensing Image Segmentation', IEEE transactions on geoscience and remote sensing, vol. 63, 5614120. https://doi.org/10.1109/TGRS.2025.3544549","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ris.utwente.nl:openaire/73b94e47-af6d-4220-b496-b475c82ecbec","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/73b94e47-af6d-4220-b496-b475c82ecbec","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lv, X, Persello, C, Li, W, Huang, X, Ming, D & Stein, A 2025, 'Deep Merge : Deep-Learning-Based Region Merging for Remote Sensing Image Segmentation', IEEE transactions on geoscience and remote sensing, vol. 63, 5614120. https://doi.org/10.1109/TGRS.2025.3544549","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G526207867","display_name":null,"funder_award_id":"10011236022401","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W318364127","https://openalex.org/W1585044132","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1965582803","https://openalex.org/W1967769689","https://openalex.org/W1977345771","https://openalex.org/W2024877884","https://openalex.org/W2042709218","https://openalex.org/W2072289174","https://openalex.org/W2076198115","https://openalex.org/W2095028777","https://openalex.org/W2110158442","https://openalex.org/W2118246710","https://openalex.org/W2118858457","https://openalex.org/W2119823327","https://openalex.org/W2121494337","https://openalex.org/W2129872026","https://openalex.org/W2135220366","https://openalex.org/W2139126945","https://openalex.org/W2151743452","https://openalex.org/W2157364932","https://openalex.org/W2168804568","https://openalex.org/W2324155672","https://openalex.org/W2340897893","https://openalex.org/W2560023338","https://openalex.org/W2567603779","https://openalex.org/W2594824325","https://openalex.org/W2646105771","https://openalex.org/W2776035257","https://openalex.org/W2799213142","https://openalex.org/W2807455572","https://openalex.org/W2810004461","https://openalex.org/W2884436604","https://openalex.org/W2891367133","https://openalex.org/W2902055884","https://openalex.org/W2945933196","https://openalex.org/W2963881378","https://openalex.org/W2970773259","https://openalex.org/W2981689412","https://openalex.org/W2990979713","https://openalex.org/W2994524071","https://openalex.org/W2995742004","https://openalex.org/W3025800305","https://openalex.org/W3068105938","https://openalex.org/W3121898985","https://openalex.org/W3137572916","https://openalex.org/W3182212068","https://openalex.org/W3182256037","https://openalex.org/W3200075728","https://openalex.org/W3203915126","https://openalex.org/W3206508052","https://openalex.org/W4214612132","https://openalex.org/W4214681150","https://openalex.org/W4221107766","https://openalex.org/W4283450732","https://openalex.org/W4302275239","https://openalex.org/W6640295612","https://openalex.org/W6717372056","https://openalex.org/W6755977528","https://openalex.org/W6797399245"],"related_works":["https://openalex.org/W4234886518","https://openalex.org/W2389591058","https://openalex.org/W2382112581","https://openalex.org/W3124036233","https://openalex.org/W4229787472","https://openalex.org/W2486541857","https://openalex.org/W2108840191","https://openalex.org/W2759366996","https://openalex.org/W2110679372","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Image":[0],"segmentation":[1,44,191],"represents":[2],"a":[3,64,194],"fundamental":[4],"step":[5],"in":[6,81,193],"analyzing":[7],"very":[8],"high-spatial-resolution":[9],"(VHR)":[10],"remote":[11,203],"sensing":[12,204],"imagery.":[13],"Its":[14],"objective":[15],"is":[16,109,146,199],"to":[17,37,48,76,100,111,129,148,171],"partition":[18],"an":[19,88,178,210],"image":[20,93],"into":[21],"segments":[22],"that":[23,67,219],"best":[24],"match":[25],"with":[26,52,87],"geo-objects.":[27],"However,":[28],"the":[29,92,113,130,134,153,159,173,222,228],"diverse":[30],"appearances":[31],"of":[32,91,155,206,212,237],"geospatial":[33],"objects":[34],"often":[35,46],"lead":[36],"interobject":[38],"homogeneity":[39],"and":[40,55,71,94,182,227,240],"intraobject":[41],"heterogeneity.":[42],"Existing":[43],"methods":[45],"struggle":[47],"accurately":[49,77,234],"segment":[50,78],"geo-objects":[51,80,236],"varying":[53,238],"shapes":[54],"scales.":[56],"To":[57],"address":[58],"these":[59],"challenges,":[60],"we":[61],"propose":[62],"DeepMerge,":[63],"novel":[65],"method":[66],"integrates":[68],"deep":[69,106],"learning":[70,107],"region":[72],"adjacency":[73],"graphs":[74],"(RAGs)":[75],"complete":[79,102],"large":[82],"VHR":[83],"images.":[84],"DeepMerge":[85,187,220],"begins":[86],"initial":[89],"over-segmentation":[90],"then":[95],"iteratively":[96],"merges":[97],"similar":[98],"regions":[99],"achieve":[101,189],"geo-object":[103,132],"segmentation.":[104,142],"A":[105,143],"model":[108],"employed":[110],"learn":[112],"similarity":[114],"between":[115,162],"adjacent":[116,126],"superpixel":[117],"pairs.":[118],"This":[119],"approach":[120],"only":[121],"requires":[122],"labels":[123],"indicating":[124],"whether":[125],"superpixels":[127],"belong":[128],"same":[131],"eliminating":[133],"need":[135],"for":[136],"object-level":[137],"annotations,":[138],"enabling":[139],"weakly":[140,195],"supervised":[141,196],"cross-scale":[144],"module":[145],"incorporated":[147],"capture":[149],"multiscale":[150],"information,":[151],"enhancing":[152],"representation":[154],"superpixels.":[156],"In":[157],"addition,":[158],"feature":[160],"distances":[161],"neighboring":[163],"super-pixels":[164],"are":[165],"deemed":[166],"as":[167],"scale":[168,184],"parameters":[169],"(thresholds)":[170],"control":[172],"merging":[174],"procedure,":[175],"thus":[176],"yielding":[177],"interpretable,":[179],"predictable,":[180],"stable,":[181],"optimal":[183],"parameter":[185],"0.5.":[186],"can":[188],"high":[190],"accuracy":[192],"manner,":[197],"which":[198],"validated":[200],"on":[201],"large-scale":[202],"images":[205],"0.55-m":[207],"resolution":[208],"covering":[209],"area":[211],"5660":[213],"km2.":[214],"The":[215],"experimental":[216],"results":[217],"demonstrate":[218],"achieves":[221],"highest":[223],"F":[224],"value":[225],"(0.9552)":[226],"lowest":[229],"total":[230],"error":[231],"(TE)":[232],"(0.0827),":[233],"segmenting":[235],"sizes":[239],"outperforming":[241],"all":[242],"competing":[243],"methods.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}