{"id":"https://openalex.org/W7115168788","doi":"https://doi.org/10.1109/tgrs.2025.3644663","title":"Subpixel Anchor Graph for Multimodal Clustering of Hyperspectral and LiDAR Data","display_name":"Subpixel Anchor Graph for Multimodal Clustering of Hyperspectral and LiDAR Data","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7115168788","doi":"https://doi.org/10.1109/tgrs.2025.3644663"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3644663","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3644663","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":"Yang Liu","orcid":"https://orcid.org/0009-0004-9364-8232"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Liu","raw_affiliation_strings":["College of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0004-9364-8232","affiliations":[{"raw_affiliation_string":"College of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shujun Liu","orcid":"https://orcid.org/0000-0003-4657-1477"},"institutions":[{"id":"https://openalex.org/I4401041622","display_name":"Chengdu Technological University","ror":"https://ror.org/04713ex73","country_code":null,"type":"education","lineage":["https://openalex.org/I4401041622"]},{"id":"https://openalex.org/I44468530","display_name":"Qingdao University of Technology","ror":"https://ror.org/01qzc0f54","country_code":"CN","type":"education","lineage":["https://openalex.org/I44468530"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shujun Liu","raw_affiliation_strings":["School of Computer Engineering, Chengdu Technological University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-4657-1477","affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Chengdu Technological University, Chengdu, China","institution_ids":["https://openalex.org/I44468530","https://openalex.org/I4401041622"]}]},{"author_position":"last","author":{"id":null,"display_name":"Luxi Xiao","orcid":"https://orcid.org/0009-0006-4828-5772"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luxi Xiao","raw_affiliation_strings":["College of Geophysics, Chengdu University of Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0006-4828-5772","affiliations":[{"raw_affiliation_string":"College of Geophysics, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":null,"apc_paid":null,"fwci":1.0273,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85085814,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9146999716758728,"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":0.9146999716758728,"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/T10057","display_name":"Face and Expression Recognition","score":0.03420000150799751,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.006000000052154064,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7229999899864197},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6564000248908997},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.588699996471405},{"id":"https://openalex.org/keywords/subpixel-rendering","display_name":"Subpixel rendering","score":0.5270000100135803},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49720001220703125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4839000105857849},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.46639999747276306},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.45590001344680786},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.38609999418258667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7286999821662903},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7229999899864197},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6564000248908997},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.588699996471405},{"id":"https://openalex.org/C68516990","wikidata":"https://www.wikidata.org/wiki/Q452912","display_name":"Subpixel rendering","level":3,"score":0.5270000100135803},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49720001220703125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4839000105857849},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.46639999747276306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46320000290870667},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.45590001344680786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43650001287460327},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.38609999418258667},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.36410000920295715},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2782000005245209},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.26339998841285706},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2605000138282776},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2596000134944916},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.2581999897956848},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3644663","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3644663","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":[],"awards":[{"id":"https://openalex.org/G7744186509","display_name":null,"funder_award_id":"202309230001","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320323826","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W297461772","https://openalex.org/W1900867691","https://openalex.org/W1968206427","https://openalex.org/W1993962865","https://openalex.org/W1997201895","https://openalex.org/W2108502868","https://openalex.org/W2132914434","https://openalex.org/W2157321686","https://openalex.org/W2165796970","https://openalex.org/W2222512263","https://openalex.org/W2318512420","https://openalex.org/W2754064832","https://openalex.org/W2766528611","https://openalex.org/W2886042776","https://openalex.org/W2898233200","https://openalex.org/W2911419410","https://openalex.org/W2988699317","https://openalex.org/W2997739739","https://openalex.org/W3019954098","https://openalex.org/W3048631361","https://openalex.org/W3091687261","https://openalex.org/W3130365209","https://openalex.org/W3136737181","https://openalex.org/W3168367808","https://openalex.org/W3205485865","https://openalex.org/W3208283713","https://openalex.org/W4206339218","https://openalex.org/W4285191214","https://openalex.org/W4285230057","https://openalex.org/W4289656123","https://openalex.org/W4293731866","https://openalex.org/W4294068629","https://openalex.org/W4313050056","https://openalex.org/W4367016851","https://openalex.org/W4384080791","https://openalex.org/W4385253134","https://openalex.org/W4385819914","https://openalex.org/W4385973234","https://openalex.org/W4385976158","https://openalex.org/W4396680544","https://openalex.org/W4401726115","https://openalex.org/W4404628516","https://openalex.org/W4406753747","https://openalex.org/W4406892669","https://openalex.org/W4407316658","https://openalex.org/W4407937102","https://openalex.org/W4407937890","https://openalex.org/W4409537021","https://openalex.org/W4410050224","https://openalex.org/W4412105550","https://openalex.org/W4412722405","https://openalex.org/W4412751299","https://openalex.org/W4413472453","https://openalex.org/W4413757873"],"related_works":[],"abstract_inverted_index":{"Traditional":[0],"anchor":[1,24,88,92,114],"graph":[2,115],"clustering":[3],"(AGC)":[4],"methods":[5,76,164],"usually":[6],"perform":[7],"suboptimally":[8],"when":[9],"dealing":[10],"with":[11],"subspace":[12],"similarity":[13],"caused":[14],"by":[15],"spectral":[16],"mixing":[17],"and":[18,86,127,151],"typically":[19],"lack":[20],"physical":[21],"interpretability":[22],"during":[23],"selection,":[25],"relying":[26],"on":[27,124,165],"complex":[28,136],"post-processing":[29],"steps.":[30],"To":[31,90,132],"address":[32],"this":[33,110],"issue,":[34],"we":[35,49,98,108,138],"introduce":[36],"hyperspectral":[37],"unmixing":[38],"(HU)":[39],"into":[40],"the":[41,51,82,100,140],"AGC":[42,78],"framework,":[43],"showing":[44],"their":[45],"inherent":[46],"equivalence.":[47],"Specifically,":[48],"proposed":[50],"Sub-Pixel":[52],"Anchor":[53,102],"Graph":[54],"Clustering":[55],"(SAGC)":[56],"method,":[57],"which":[58],"explicitly":[59],"models":[60],"sub-pixel":[61,96],"information":[62,150],"from":[63],"mixed":[64],"spectra":[65],"to":[66,77,112,142,162],"endmembers":[67],"for":[68,80],"clustering.":[69],"It":[70],"allows":[71],"seamless":[72],"migration":[73],"of":[74,84],"HU":[75],"tasks":[79],"determining":[81],"number":[83],"anchors":[85],"guiding":[87],"selection.":[89],"enhance":[91],"diversity":[93],"while":[94,169],"preserving":[95],"information,":[97],"design":[99],"Maximum":[101],"Diversity":[103],"Selection":[104],"Strategy":[105],"(MADSS).":[106],"Finally,":[107],"apply":[109],"framework":[111],"HS-LiDAR":[113,167],"clustering,":[116],"providing":[117],"an":[118,128],"implicit":[119],"spatial":[120,149],"regularization":[121],"method":[122,141],"based":[123],"unified":[125],"abundances":[126],"efficient":[129],"solving":[130],"strategy.":[131],"improve":[133],"robustness":[134],"in":[135],"scenarios,":[137],"extend":[139],"its":[143],"deep":[144],"counterpart":[145],"(DSAGC),":[146],"effectively":[147],"modeling":[148],"nonlinear":[152],"features.":[153],"Experimental":[154],"results":[155],"show":[156],"that":[157],"SAGC":[158],"achieves":[159],"performance":[160],"comparable":[161],"state-of-the-art":[163],"three":[166],"datasets,":[168],"DSAGC":[170],"delivers":[171],"significant":[172],"improvements.":[173],"Code":[174],"is":[175],"available":[176],"at:":[177],"https://github.com/Liujehong/SAGC.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-12-15T00:00:00"}