{"id":"https://openalex.org/W4388118221","doi":"https://doi.org/10.23919/eusipco58844.2023.10290100","title":"Model-Aware Deep Learning for the Clustering of Hyperspectral Images with Context Preservation","display_name":"Model-Aware Deep Learning for the Clustering of Hyperspectral Images with Context Preservation","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4388118221","doi":"https://doi.org/10.23919/eusipco58844.2023.10290100"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco58844.2023.10290100","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco58844.2023.10290100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://biblio.ugent.be/publication/01HCFN092RRX2957YQWAFX71E6/file/01HMEF3ZY4488Q4V5VD5GA8S4P.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000414053","display_name":"Xianlu Li","orcid":"https://orcid.org/0009-0001-4149-2887"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Xianlu Li","raw_affiliation_strings":["Ghent University,Department of Telecommunications and Information Processing,Belgium","Department of Telecommunications and Information Processing, Ghent University, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University,Department of Telecommunications and Information Processing,Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085641593","display_name":"Nicolas Nadisic","orcid":"https://orcid.org/0000-0002-5993-7194"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Nicolas Nadisic","raw_affiliation_strings":["Ghent University,Department of Telecommunications and Information Processing,Belgium","Department of Telecommunications and Information Processing, Ghent University, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University,Department of Telecommunications and Information Processing,Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050449194","display_name":"Shaoguang Huang","orcid":"https://orcid.org/0000-0001-5439-5018"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoguang Huang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences,Wuhan,China","School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences,Wuhan,China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043511500","display_name":"Nikos Deligiannis","orcid":"https://orcid.org/0000-0001-9300-5860"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]},{"id":"https://openalex.org/I4210114974","display_name":"IMEC","ror":"https://ror.org/02kcbn207","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I4210114974"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Nikos Deligiannis","raw_affiliation_strings":["Vrije Universiteit Brussel,Department Electronics and Informatics,Belgium","Department Electronics and Informatics, Vrije Universiteit Brussel, Belgium","imec, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,Department Electronics and Informatics,Belgium","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"Department Electronics and Informatics, Vrije Universiteit Brussel, Belgium","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"imec, Leuven, Belgium","institution_ids":["https://openalex.org/I4210114974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031078128","display_name":"Aleksandra Pi\u017eurica","orcid":"https://orcid.org/0000-0002-9322-4999"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Aleksandra Pi\u017eurica","raw_affiliation_strings":["Ghent University,Department of Telecommunications and Information Processing,Belgium","Department of Telecommunications and Information Processing, Ghent University, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University,Department of Telecommunications and Information Processing,Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Telecommunications and Information Processing, Ghent University, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"885","last_page":"889"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9793999791145325,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9757000207901001,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8374381065368652},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7875604629516602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6945797204971313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6891446113586426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6469665765762329},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5564466714859009},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5528264045715332},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5471285581588745},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5058181285858154},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.49740031361579895},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.460987389087677},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4417835474014282},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44008758664131165},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24322935938835144},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07843160629272461}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8374381065368652},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7875604629516602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6945797204971313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6891446113586426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6469665765762329},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5564466714859009},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5528264045715332},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5471285581588745},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5058181285858154},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.49740031361579895},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.460987389087677},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4417835474014282},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44008758664131165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24322935938835144},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07843160629272461},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.23919/eusipco58844.2023.10290100","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco58844.2023.10290100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:archive.ugent.be:01HCFN092RRX2957YQWAFX71E6","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-01HCFN092RRX2957YQWAFX71E6","pdf_url":"https://biblio.ugent.be/publication/01HCFN092RRX2957YQWAFX71E6/file/01HMEF3ZY4488Q4V5VD5GA8S4P.pdf","source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9789464593600","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"doi:10.5281/zenodo.11117445","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.11117445","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:archive.ugent.be:01HCFN092RRX2957YQWAFX71E6","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-01HCFN092RRX2957YQWAFX71E6","pdf_url":"https://biblio.ugent.be/publication/01HCFN092RRX2957YQWAFX71E6/file/01HMEF3ZY4488Q4V5VD5GA8S4P.pdf","source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9789464593600","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4388118221.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1977556410","https://openalex.org/W1993962865","https://openalex.org/W2073459066","https://openalex.org/W2113076747","https://openalex.org/W2313932751","https://openalex.org/W2555332322","https://openalex.org/W2736773830","https://openalex.org/W2892017453","https://openalex.org/W2961290969","https://openalex.org/W2963365397","https://openalex.org/W2964074409","https://openalex.org/W2982673782","https://openalex.org/W2984701870","https://openalex.org/W3006938728","https://openalex.org/W3075397214","https://openalex.org/W3127593446","https://openalex.org/W3133902371","https://openalex.org/W3135512617","https://openalex.org/W3209156169","https://openalex.org/W3212176979","https://openalex.org/W4285191214","https://openalex.org/W4292363360","https://openalex.org/W4312459443","https://openalex.org/W4386179745","https://openalex.org/W6644682428","https://openalex.org/W6668990524","https://openalex.org/W6685380521","https://openalex.org/W6744043827","https://openalex.org/W6769378220","https://openalex.org/W6790324123","https://openalex.org/W6803760252"],"related_works":["https://openalex.org/W227974271","https://openalex.org/W2977728051","https://openalex.org/W2968737478","https://openalex.org/W2185081213","https://openalex.org/W88288160","https://openalex.org/W2761926807","https://openalex.org/W2131828344","https://openalex.org/W2985124601","https://openalex.org/W3181754176","https://openalex.org/W3023007226"],"abstract_inverted_index":{"Deep":[0,70],"subspace":[1,108,179],"clustering":[2,8,17,109],"is":[3,118,138],"an":[4],"effective":[5],"method":[6],"for":[7,96,111,178],"high-dimensional":[9],"data,":[10],"and":[11,54,90,98,134],"it":[12,58],"provides":[13],"state-of-the-art":[14,176],"results":[15],"in":[16,37,48,120],"hyperspectral":[18,112,170],"images":[19,113],"(HSI).":[20],"However,":[21],"these":[22,62],"methods":[23,63,177],"typically":[24],"suffer":[25],"from":[26],"the":[27,30,40,77,115,121,130,135,153],"size":[28,38],"of":[29,79],"so-called":[31],"self-expression":[32],"matrix":[33],"that":[34,144],"increases":[35],"quadratically":[36],"with":[39,147,158],"image":[41],"to":[42,60,64,94,151],"be":[43],"clustered.":[44],"This":[45],"can":[46],"result":[47],"significant":[49],"demands":[50],"on":[51,75,168],"computing":[52],"power":[53],"storage":[55],"capacity,":[56],"making":[57],"challenging":[59],"apply":[61],"large-scale":[65],"data.":[66],"Recently":[67],"emerging":[68],"Efficient":[69],"Embedded":[71],"Subspace":[72],"Clustering":[73],"focuses":[74],"learning":[76],"basis":[78],"different":[80],"subspaces":[81],"which":[82],"need":[83],"much":[84],"fewer":[85],"parameters.":[86],"Here,":[87],"we":[88],"extend":[89],"generalize":[91],"this":[92],"approach":[93],"account":[95],"local":[97,131],"non-local":[99,136],"spatial":[100,132],"context.":[101],"We":[102],"propose":[103],"a":[104,141,163],"structured":[105],"model-aware":[106],"deep":[107],"network":[110],"where":[114],"contextual":[116],"information":[117],"captured":[119],"appropriately":[122],"defined":[123],"loss":[124,128,143],"functions.":[125],"A":[126],"self-supervised":[127],"captures":[129],"structure,":[133],"structure":[137],"incorporated":[139],"through":[140],"contrastive":[142],"encourages":[145],"pixels":[146,157],"small":[148],"feature":[149,160],"distances":[150,161],"have":[152,162],"same":[154],"prediction,":[155],"while":[156],"large":[159],"distinct":[164],"prediction.":[165],"The":[166],"experiments":[167],"real-world":[169],"datasets":[171],"demonstrate":[172],"clear":[173],"advantages":[174],"over":[175],"clustering.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}