{"id":"https://openalex.org/W4402259516","doi":"https://doi.org/10.1109/igarss53475.2024.10641679","title":"Unsupervised Nonlinear Hyperspectral Unmixing Based on an Extended Multilinear Mixing Model-Inspired Dual-Stream Network","display_name":"Unsupervised Nonlinear Hyperspectral Unmixing Based on an Extended Multilinear Mixing Model-Inspired Dual-Stream Network","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402259516","doi":"https://doi.org/10.1109/igarss53475.2024.10641679"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641679","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10641679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5100780136","display_name":"Minglei Li","orcid":"https://orcid.org/0000-0002-2051-9905"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minglei Li","raw_affiliation_strings":["Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721239","display_name":"Linwei Li","orcid":"https://orcid.org/0000-0002-8406-8322"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linwei Li","raw_affiliation_strings":["Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059575276","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0003-4748-6426"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083412798","display_name":"Bo Hu","orcid":"https://orcid.org/0000-0001-6348-010X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Hu","raw_affiliation_strings":["Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University,Key Laboratory for Information Science of Electromagnetic Waves (MoE),Shanghai,China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9033","last_page":"9036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9966999888420105,"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":0.9911999702453613,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8942968845367432},{"id":"https://openalex.org/keywords/multilinear-map","display_name":"Multilinear map","score":0.8903790712356567},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6779853701591492},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.6091470718383789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5860597491264343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5531880259513855},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5014078617095947},{"id":"https://openalex.org/keywords/multilinear-algebra","display_name":"Multilinear algebra","score":0.4657028317451477},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4469003677368164},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21177193522453308},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08265674114227295}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8942968845367432},{"id":"https://openalex.org/C84392682","wikidata":"https://www.wikidata.org/wiki/Q1952404","display_name":"Multilinear map","level":2,"score":0.8903790712356567},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6779853701591492},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.6091470718383789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5860597491264343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5531880259513855},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5014078617095947},{"id":"https://openalex.org/C60321788","wikidata":"https://www.wikidata.org/wiki/Q1197190","display_name":"Multilinear algebra","level":5,"score":0.4657028317451477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4469003677368164},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21177193522453308},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08265674114227295},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C136119220","wikidata":"https://www.wikidata.org/wiki/Q1000660","display_name":"Algebra over a field","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C169171071","wikidata":"https://www.wikidata.org/wiki/Q5449241","display_name":"Filtered algebra","level":3,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C138354692","wikidata":"https://www.wikidata.org/wiki/Q1231309","display_name":"Division algebra","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641679","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10641679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1957094454","https://openalex.org/W2127062304","https://openalex.org/W2157321686","https://openalex.org/W2811009023","https://openalex.org/W2894115892","https://openalex.org/W3110749113","https://openalex.org/W3205148564","https://openalex.org/W4206259850","https://openalex.org/W4293731930","https://openalex.org/W4386124082"],"related_works":["https://openalex.org/W2071105597","https://openalex.org/W2242909499","https://openalex.org/W2405717268","https://openalex.org/W2946637708","https://openalex.org/W4235893778","https://openalex.org/W2100779717","https://openalex.org/W3189506985","https://openalex.org/W2901391673","https://openalex.org/W4376274937","https://openalex.org/W3022422766"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,36,67,113,124],"challenges":[3],"posed":[4],"by":[5],"mixed":[6],"pixels":[7],"in":[8,17],"hyper-spectral":[9],"images":[10],"(HSIs),":[11],"significant":[12],"advancements":[13],"have":[14],"been":[15],"made":[16],"both":[18,104],"model-":[19],"and":[20,32,97],"deep":[21],"learning-based":[22],"unmixing":[23,39,69],"methods.":[24,134],"However,":[25],"issues":[26],"such":[27],"as":[28],"complex":[29],"computational":[30],"processes":[31],"limited":[33],"interpretability,":[34],"hinder":[35],"improvement":[37],"of":[38,63,127],"performance.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44],"propose":[45],"an":[46,74,78,82],"extended":[47],"multilinear":[48],"mixing":[49],"(EMLM)":[50],"model-inspired":[51],"dual-stream":[52,88],"network":[53,92],"for":[54,66],"unsupervised":[55],"nonlinear":[56],"hyperspectral":[57,121],"unmixing.":[58],"The":[59],"alternating":[60],"direction":[61],"method":[62,130],"multipliers":[64],"(ADMM)":[65],"EMLM-based":[68,79],"is":[70],"unfolded":[71],"to":[72,77,107],"construct":[73],"encoder,":[75],"connected":[76],"decoder,":[80],"creating":[81],"autoencoder-like":[83],"architecture.":[84],"Within":[85],"a":[86],"weight-sharing":[87],"framework,":[89],"two":[90,120],"same":[91],"branches":[93,105],"process":[94],"original":[95],"HSIs":[96],"superpixel-averaging-based":[98],"coarse":[99],"HSIs,":[100],"respectively.":[101],"Estimates":[102],"from":[103],"contribute":[106],"local":[108],"spatial":[109],"similarity":[110],"regularizers,":[111],"enhancing":[112],"network\u2019s":[114],"loss":[115],"function.":[116],"Experimental":[117],"results":[118],"on":[119],"datasets":[122],"demonstrate":[123],"superior":[125],"performance":[126],"our":[128],"proposed":[129],"over":[131],"other":[132],"state-of-the-art":[133]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}