{"id":"https://openalex.org/W7092283879","doi":"https://doi.org/10.1109/tgrs.2025.3622749","title":"Learning Frequency-Domain Fusion for Multimodal Remote Sensing Semantic Segmentation","display_name":"Learning Frequency-Domain Fusion for Multimodal Remote Sensing Semantic Segmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7092283879","doi":"https://doi.org/10.1109/tgrs.2025.3622749"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3622749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3622749","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":null,"display_name":"Guangsheng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guangsheng Chen","raw_affiliation_strings":["College of Computer and Control Engineering, Northeast Forestry University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Northeast Forestry University, Harbin, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fangyu Sun","orcid":"https://orcid.org/0009-0006-4752-1358"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangyu Sun","raw_affiliation_strings":["College of Computer and Control Engineering, Northeast Forestry University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Northeast Forestry University, Harbin, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weipeng Jing","orcid":"https://orcid.org/0000-0001-7933-6946"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weipeng Jing","raw_affiliation_strings":["College of Computer and Control Engineering, Northeast Forestry University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Northeast Forestry University, Harbin, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weitao Zou","orcid":"https://orcid.org/0000-0003-2834-4289"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weitao Zou","raw_affiliation_strings":["College of Computer and Control Engineering, Northeast Forestry University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Northeast Forestry University, Harbin, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Donglin Di","orcid":"https://orcid.org/0000-0002-2270-3378"},"institutions":[{"id":"https://openalex.org/I4210158408","display_name":"Matrix Research (United States)","ror":"https://ror.org/04mw0p229","country_code":"US","type":"company","lineage":["https://openalex.org/I4210158408"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donglin Di","raw_affiliation_strings":["DZ Matrix, Beijing, China"],"affiliations":[{"raw_affiliation_string":"DZ Matrix, Beijing, China","institution_ids":["https://openalex.org/I4210158408"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yang Song","orcid":"https://orcid.org/0000-0003-1283-1672"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yang Song","raw_affiliation_strings":["School of Computer Science and Engineering, UNSW Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, UNSW Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":null,"display_name":"Lei Fan","orcid":"https://orcid.org/0000-0001-9472-7152"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lei Fan","raw_affiliation_strings":["School of Computer Science and Engineering, UNSW Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, UNSW Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47689461"],"apc_list":null,"apc_paid":null,"fwci":1.2331,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87277991,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.5375999808311462,"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":0.5375999808311462,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.16519999504089355,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1509999930858612,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5526999831199646},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5428000092506409},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5389999747276306},{"id":"https://openalex.org/keywords/semantic-mapping","display_name":"Semantic mapping","score":0.486299991607666},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.46059998869895935},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.44609999656677246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4124999940395355},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.37860000133514404},{"id":"https://openalex.org/keywords/remote-sensing-application","display_name":"Remote sensing application","score":0.375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8409000039100647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.592199981212616},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5526999831199646},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5389999747276306},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.486299991607666},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.38179999589920044},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.375},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36809998750686646},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.28529998660087585},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2840999960899353},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.2632000148296356},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3622749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3622749","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":[{"id":"https://metadata.un.org/sdg/10","score":0.7447121739387512,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1565402342","https://openalex.org/W2760923572","https://openalex.org/W2947400201","https://openalex.org/W3010761711","https://openalex.org/W3034727830","https://openalex.org/W3048631361","https://openalex.org/W3081345704","https://openalex.org/W3127751679","https://openalex.org/W3193940683","https://openalex.org/W4200556575","https://openalex.org/W4226418836","https://openalex.org/W4226530543","https://openalex.org/W4229058281","https://openalex.org/W4251556321","https://openalex.org/W4283450732","https://openalex.org/W4289551976","https://openalex.org/W4310582166","https://openalex.org/W4367294505","https://openalex.org/W4378375546","https://openalex.org/W4384917159","https://openalex.org/W4385245566","https://openalex.org/W4386071531","https://openalex.org/W4386179772","https://openalex.org/W4386590839","https://openalex.org/W4391992568","https://openalex.org/W4392543906","https://openalex.org/W4394938945","https://openalex.org/W4396680498","https://openalex.org/W4399618753","https://openalex.org/W4400448116","https://openalex.org/W4400448320","https://openalex.org/W4400579361","https://openalex.org/W4401357939","https://openalex.org/W4401879614","https://openalex.org/W4402753319","https://openalex.org/W4403054572","https://openalex.org/W4404101926","https://openalex.org/W4404408958","https://openalex.org/W4406610749","https://openalex.org/W4406892479","https://openalex.org/W4407937888","https://openalex.org/W4408612723","https://openalex.org/W4408703306","https://openalex.org/W4409225836","https://openalex.org/W4409348648","https://openalex.org/W4411089481","https://openalex.org/W4413145660","https://openalex.org/W6941273861","https://openalex.org/W7091363795"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"remote":[1,168],"sensing":[2,14,169],"data":[3],"substantially":[4],"enhance":[5],"semantic":[6,29,160],"segmentation":[7],"accuracy":[8,176],"by":[9],"providing":[10],"complementary":[11],"information":[12],"across":[13,177],"modalities.":[15],"However,":[16],"fully":[17],"exploiting":[18],"and":[19,84,95,98,111,134,151],"effectively":[20],"fusing":[21,96],"features":[22],"from":[23,50],"different":[24],"modalities":[25],"to":[26,39,47,92,108,129,154],"capture":[27],"comprehensive":[28],"representations":[30,45,153],"remains":[31],"a":[32,61,123],"challenge.":[33],"Most":[34],"existing":[35],"methods":[36],"restrict":[37],"interactions":[38],"the":[40,73,79,85],"spatial":[41],"domain,":[42],"making":[43],"their":[44],"vulnerable":[46],"heterogeneity":[48],"arising":[49],"distinct":[51],"imaging":[52],"mechanisms.":[53],"To":[54],"address":[55],"these":[56],"issues,":[57],"we":[58],"propose":[59],"FDMF-Net,":[60],"Frequency-domain":[62],"Decoupled":[63],"Modality":[64,80],"Fusion":[65,88],"network.":[66],"Our":[67],"approach":[68],"comprises":[69],"three":[70],"key":[71],"modules:":[72],"Amplitude":[74],"Spectrum":[75],"Decoupling":[76],"module":[77,82,89,104,121],"(ASD),":[78],"Enhancement":[81],"(ME),":[83],"Low-Frequency-Guided":[86],"Feature":[87],"(LFGF),":[90],"dedicated":[91],"extracting,":[93],"enhancing,":[94],"modality-invariant":[97,110,133],"specific":[99,152],"representations,":[100,136],"respectively.":[101],"The":[102,119,141,180],"ASD":[103],"performs":[105],"frequency-domain":[106],"decomposition":[107],"separate":[109],"modality-specific":[112,135],"features,":[113],"promoting":[114],"more":[115,131],"effective":[116],"cross-modal":[117],"complementarity.":[118],"ME":[120],"introduces":[122],"mutual":[124],"information-based":[125],"feature":[126,139,156],"enhancement":[127],"scheme":[128],"obtain":[130],"robust":[132],"thereby":[137],"improving":[138],"discriminability.":[140],"LFGF":[142],"module,":[143],"based":[144],"on":[145,164],"an":[146],"attention":[147],"mechanism,":[148],"fuses":[149],"shared":[150],"generate":[155],"maps":[157],"with":[158],"richer":[159],"information.":[161],"Extensive":[162],"evaluations":[163],"multiple":[165],"standard":[166],"multimodal":[167],"datasets":[170],"demonstrate":[171],"that":[172],"FDMF-Net":[173],"achieves":[174],"state-of-the-art":[175],"several":[178],"benchmarks.":[179],"code":[181],"is":[182],"available":[183],"at":[184],"https://github.com/fy-sun/FDMF-Net.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-18T00:00:00"}
