{"id":"https://openalex.org/W7101705226","doi":"https://doi.org/10.1109/lgrs.2025.3626341","title":"DPCM-HAEM: A Hyperspectral Image Unmixing Method Based on Dual-Path Convolution Module and Hybrid Attention Enhancement Mechanism","display_name":"DPCM-HAEM: A Hyperspectral Image Unmixing Method Based on Dual-Path Convolution Module and Hybrid Attention Enhancement Mechanism","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7101705226","doi":"https://doi.org/10.1109/lgrs.2025.3626341"},"language":null,"primary_location":{"id":"doi:10.1109/lgrs.2025.3626341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3626341","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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":"Yaohai Lin","orcid":"https://orcid.org/0000-0002-1654-1130"},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaohai Lin","raw_affiliation_strings":["Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0002-1654-1130","affiliations":[{"raw_affiliation_string":"Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Youzhuang Lin","orcid":"https://orcid.org/0009-0008-2141-5447"},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youzhuang Lin","raw_affiliation_strings":["Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0009-0008-2141-5447","affiliations":[{"raw_affiliation_string":"Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wanhan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanhan Wu","raw_affiliation_strings":["Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zipeng You","orcid":null},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zipeng You","raw_affiliation_strings":["Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Changcai Yang","orcid":"https://orcid.org/0000-0003-0996-9718"},"institutions":[{"id":"https://openalex.org/I61057504","display_name":"Fujian Agriculture and Forestry University","ror":"https://ror.org/04kx2sy84","country_code":"CN","type":"education","lineage":["https://openalex.org/I61057504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changcai Yang","raw_affiliation_strings":["Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0003-0996-9718","affiliations":[{"raw_affiliation_string":"Digital Fujian Research Institute of Big Data for Agriculture and Forestry, College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I61057504"]}]},{"author_position":"last","author":{"id":null,"display_name":"Minghao Zhu","orcid":"https://orcid.org/0000-0002-3523-8233"},"institutions":[{"id":"https://openalex.org/I148099405","display_name":"Xi'an University of Architecture and Technology","ror":"https://ror.org/04v2j2k71","country_code":"CN","type":"education","lineage":["https://openalex.org/I148099405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghao Zhu","raw_affiliation_strings":["College of Information and Control Engineering, Xi&#x2019;an University of Architecture and Technology, Xi&#x2019;an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-3523-8233","affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering, Xi&#x2019;an University of Architecture and Technology, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I148099405"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I61057504"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55347343,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11745","display_name":"Potato Plant Research","score":0.07209999859333038,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11745","display_name":"Potato Plant Research","score":0.07209999859333038,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10385","display_name":"Plant Diversity and Evolution","score":0.032600000500679016,"subfield":{"id":"https://openalex.org/subfields/1105","display_name":"Ecology, Evolution, Behavior and Systematics"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.03200000151991844,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8697999715805054},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7045000195503235},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6757000088691711},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6668000221252441},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5615000128746033},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5404999852180481},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49619999527931213},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3336000144481659}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8697999715805054},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7603999972343445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7448999881744385},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7045000195503235},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6757000088691711},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6668000221252441},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5615000128746033},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5404999852180481},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49619999527931213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3813999891281128},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.2849999964237213},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.28040000796318054},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27309998869895935},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3626341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3626341","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2780802765","display_name":null,"funder_award_id":"KH230409A","funder_id":"https://openalex.org/F4320317847","funder_display_name":"Raytheon Technologies"}],"funders":[{"id":"https://openalex.org/F4320317847","display_name":"Raytheon Technologies","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W625476304","https://openalex.org/W2027878671","https://openalex.org/W2101837437","https://openalex.org/W2111752896","https://openalex.org/W2114486983","https://openalex.org/W2144881411","https://openalex.org/W2157321686","https://openalex.org/W2169924573","https://openalex.org/W2894115892","https://openalex.org/W3028000844","https://openalex.org/W3137191419","https://openalex.org/W3189122062","https://openalex.org/W4210555639","https://openalex.org/W4211249244","https://openalex.org/W4289656123","https://openalex.org/W4289752563","https://openalex.org/W4292974214","https://openalex.org/W4391020695"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3],"learning-based":[4],"methods":[5],"have":[6,31],"attracted":[7],"considerable":[8],"attention":[9,108],"in":[10,34,43,156],"hyperspectral":[11,157],"image":[12,158],"unmixing(HU)":[13],"tasks":[14],"due":[15],"to":[16,81,95,113],"their":[17],"robust":[18],"feature":[19,45,73,124],"extraction":[20,46,90],"and":[21,47,66,85,99,117,136,154],"powerful":[22],"fitting":[23],"capabilities.":[24],"Among":[25],"them,":[26],"Convolutional":[27],"Neural":[28],"Networks":[29],"(CNNs)":[30],"gained":[32],"popularity":[33],"HU":[35],"research.":[36],"However,":[37],"they":[38],"still":[39],"suffer":[40],"from":[41,102],"limitations":[42],"spatial":[44,98,116],"effective":[48,123],"integration":[49],"of":[50],"spatial-spectral":[51,89,128],"information.":[52,87],"To":[53],"address":[54],"these":[55],"issues,":[56],"a":[57,75,106],"Hyperspectral":[58],"Image":[59],"Unmixing":[60],"Method":[61],"Based":[62],"on":[63,132],"Dual-Path":[64],"Convolution":[65],"Hybrid":[67],"Attention":[68],"Enhancement":[69],"Mechanism":[70],"is":[71,79,92,111,162],"proposed.Before":[72],"extraction,":[74],"dual-path":[76],"convolution":[77],"module":[78,91],"introduced":[80],"capture":[82],"both":[83],"local":[84],"global":[86],"The":[88],"then":[93],"employed":[94],"jointly":[96],"extract":[97],"spectral":[100,118],"features":[101],"the":[103,114,142],"data.":[104],"Finally,":[105],"hybrid":[107],"enhancement":[109],"mechanism":[110],"applied":[112],"obtained":[115],"features,":[119],"thereby":[120],"providing":[121],"more":[122],"representations":[125],"for":[126],"subsequent":[127],"fusion.":[129],"Experimental":[130],"results":[131],"three":[133],"real":[134],"datasets":[135],"one":[137],"synthetic":[138],"dataset":[139],"demonstrate":[140],"that":[141],"proposed":[143],"method":[144],"significantly":[145],"outperforms":[146],"six":[147],"others":[148],"unmixing":[149,159],"methods,":[150],"validating":[151],"its":[152],"effectiveness":[153],"potential":[155],"tasks.The":[160],"code":[161],"available":[163],"at":[164],"https://github.com/luckyyuanzhi/DPCM-HAEM.":[165]},"counts_by_year":[],"updated_date":"2025-11-15T23:13:30.683059","created_date":"2025-10-29T00:00:00"}
