{"id":"https://openalex.org/W2994545211","doi":"https://doi.org/10.1109/whispers.2019.8920854","title":"The Application Of Subspace Clustering Algorithms In Drill-Core Hyperspectral Domaining","display_name":"The Application Of Subspace Clustering Algorithms In Drill-Core Hyperspectral Domaining","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2994545211","doi":"https://doi.org/10.1109/whispers.2019.8920854","mag":"2994545211"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2019.8920854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2019.8920854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","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/A5086519517","display_name":"Kasra Rafiezadeh Shahi","orcid":"https://orcid.org/0000-0003-3666-4223"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kasra Rafiezadeh Shahi","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055884274","display_name":"Mahdi Khodadadzadeh","orcid":"https://orcid.org/0000-0001-7899-738X"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mahdi Khodadadzadeh","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080950597","display_name":"Raimon Tolosana\u2010Delgado","orcid":"https://orcid.org/0000-0001-9847-0462"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Raimon Tolosana-delgado","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043971532","display_name":"Laura Tu\u015fa","orcid":null},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Laura Tusa","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067490750","display_name":"Richard Gloaguen","orcid":"https://orcid.org/0000-0002-4383-473X"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Richard Gloaguen","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"10789","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9983999729156494,"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":0.9983999729156494,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9835000038146973,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.869767963886261},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6806918978691101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6568089723587036},{"id":"https://openalex.org/keywords/drill","display_name":"Drill","score":0.6391302943229675},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5362405776977539},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5204260945320129},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4549911916255951},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.4490540325641632},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.44590699672698975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43335139751434326},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.42625653743743896},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.41533440351486206},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38588035106658936},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11225289106369019}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.869767963886261},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6806918978691101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6568089723587036},{"id":"https://openalex.org/C173736775","wikidata":"https://www.wikidata.org/wiki/Q58964","display_name":"Drill","level":2,"score":0.6391302943229675},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5362405776977539},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5204260945320129},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4549911916255951},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.4490540325641632},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.44590699672698975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43335139751434326},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.42625653743743896},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.41533440351486206},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38588035106658936},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11225289106369019},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2019.8920854","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2019.8920854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6499999761581421,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1964050442","https://openalex.org/W1975956815","https://openalex.org/W1993962865","https://openalex.org/W1997201895","https://openalex.org/W2010797000","https://openalex.org/W2110726819","https://openalex.org/W2313932751","https://openalex.org/W2765674087","https://openalex.org/W2778896011","https://openalex.org/W2896299446","https://openalex.org/W2898190873","https://openalex.org/W3020865758","https://openalex.org/W4235169531"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W3144143113","https://openalex.org/W4306940721","https://openalex.org/W2160785859","https://openalex.org/W4301002638","https://openalex.org/W2938348585","https://openalex.org/W3022637481","https://openalex.org/W3120229345","https://openalex.org/W1979094538","https://openalex.org/W3161541212"],"abstract_inverted_index":{"Diamond":[0],"drilling":[1],"is":[2,44,202],"used":[3],"in":[4,42,84,108],"the":[5,40,48,58,64,85,104,151,155,181,184,210],"mining":[6,86],"industry":[7],"to":[8,25,34,56],"extract":[9],"drill-cores":[10,16,66,107],"for":[11,103,122],"characterising":[12],"mineral":[13],"deposits.":[14],"Traditionally,":[15],"are":[17,51,120,161,178],"visually":[18],"analysed":[19],"by":[20],"an":[21,100],"on-site":[22],"geologist,":[23],"subjected":[24,33],"geochemical":[26],"analyses,":[27,65],"and":[28,47,62,72,111,171,200],"then,":[29,73],"few":[30],"representative":[31],"samples":[32,43,61,166],"additional":[35],"high-resolution":[36],"mineralogical":[37,49,170],"studies.":[38],"However,":[39],"choice":[41,59],"frequently":[45],"subjective":[46],"analyses":[50,75],"highly":[52],"time-consuming.":[53],"In":[54,126],"order":[55],"optimize":[57],"of":[60,106,117,154,183],"accelerate":[63],"can":[67,76],"be":[68,77],"partitioned":[69],"into":[70],"domains,":[71],"laboratory":[74],"carried":[78],"out":[79],"on":[80,150,163],"selected":[81],"domains.":[82],"Nevertheless,":[83],"industry,":[87],"automatic":[88,123],"drill-core":[89,124,165,198],"domaining":[90],"still":[91],"remains":[92],"a":[93,109],"challenge.":[94],"Recently,":[95],"hyperspectral":[96,156],"imaging":[97],"has":[98],"become":[99],"important":[101],"technique":[102],"analysis":[105],"non-invasive":[110],"non-destructive":[112],"manner.":[113],"Several":[114],"clustering":[115,134,139,144,159,176,186,194,211],"algorithms":[116,135,147,177,195],"hyper-spectral":[118],"data":[119],"proposed":[121],"domaining.":[125],"this":[127],"paper,":[128],"we":[129],"suggest":[130],"using":[131],"advanced":[132],"subspace":[133,138,143,175,193],"(i.e.,":[136],"sparse":[137,142],"algorithm,":[140],"spectral-spatial":[141],"algorithm).":[145],"These":[146],"work":[148],"based":[149],"self-representation":[152],"property":[153],"data.":[157],"The":[158,174],"methods":[160],"tested":[162],"two":[164],"which":[167],"present":[168],"different":[169],"structural":[172],"features.":[173],"compared":[179],"with":[180],"result":[182],"K-means":[185],"algorithm.":[187],"Our":[188],"experimental":[189],"results":[190],"show":[191],"that":[192,204],"provide":[196],"accurate":[197],"domains":[199],"it":[201],"shown":[203],"including":[205],"spatial":[206],"information":[207],"significantly":[208],"improves":[209],"results.":[212]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}