{"id":"https://openalex.org/W4285013502","doi":"https://doi.org/10.3390/rs14143317","title":"Improving Image Clustering through Sample Ranking and Its Application to Remote Sensing Images","display_name":"Improving Image Clustering through Sample Ranking and Its Application to Remote Sensing Images","publication_year":2022,"publication_date":"2022-07-09","ids":{"openalex":"https://openalex.org/W4285013502","doi":"https://doi.org/10.3390/rs14143317"},"language":"en","primary_location":{"id":"doi:10.3390/rs14143317","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14143317","pdf_url":"https://www.mdpi.com/2072-4292/14/14/3317/pdf?version=1657611921","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/14/3317/pdf?version=1657611921","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100747703","display_name":"Qinglin Li","orcid":"https://orcid.org/0000-0003-3002-1702"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinglin Li","raw_affiliation_strings":["College of Electronic and Information Engineering, Shenzhen University, Shenzhen 518052, China","Guangdong Key Lab for Intelligent Information Processing, Shenzhen 518052, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Shenzhen University, Shenzhen 518052, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Key Lab for Intelligent Information Processing, Shenzhen 518052, China","institution_ids":["https://openalex.org/I4210142539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114259459","display_name":"Guoping Qiu","orcid":"https://orcid.org/0000-0002-5877-5648"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210104064","display_name":"Shenzhen Academy of Robotics","ror":"https://ror.org/01h027j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210104064"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guoping Qiu","raw_affiliation_strings":["College of Electronic and Information Engineering, Shenzhen University, Shenzhen 518052, China","Guangdong Key Lab for Intelligent Information Processing, Shenzhen 518052, China","Pengcheng Laboratory, Shenzhen 518055, China","Shenzhen Institute of AI and Robotics for Society, Shenzhen 518172, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Shenzhen University, Shenzhen 518052, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Key Lab for Intelligent Information Processing, Shenzhen 518052, China","institution_ids":["https://openalex.org/I4210142539"]},{"raw_affiliation_string":"Pengcheng Laboratory, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Shenzhen Institute of AI and Robotics for Society, Shenzhen 518172, China","institution_ids":["https://openalex.org/I4210104064"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114259459"],"corresponding_institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4210104064","https://openalex.org/I4210136793","https://openalex.org/I4210142539"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.1097,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43234185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"14","issue":"14","first_page":"3317","last_page":"3317"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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":0.9954000115394592,"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":0.7793381214141846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7483810186386108},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7254064679145813},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6894810199737549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5485981702804565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5025622844696045},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4962623715400696},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4926212430000305},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.46833205223083496},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45969358086586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3335581421852112},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32374727725982666},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1141684353351593}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7793381214141846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483810186386108},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7254064679145813},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6894810199737549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5485981702804565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5025622844696045},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4962623715400696},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4926212430000305},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.46833205223083496},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45969358086586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3335581421852112},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32374727725982666},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1141684353351593},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/rs14143317","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14143317","pdf_url":"https://www.mdpi.com/2072-4292/14/14/3317/pdf?version=1657611921","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2209.12621","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.12621","pdf_url":"https://arxiv.org/pdf/2209.12621","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:20491debfedc4f39a8b8b1af5987d399","is_oa":true,"landing_page_url":"https://doaj.org/article/20491debfedc4f39a8b8b1af5987d399","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 14, p 3317 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/14/3317/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14143317","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14143317","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14143317","pdf_url":"https://www.mdpi.com/2072-4292/14/14/3317/pdf?version=1657611921","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G8617609110","display_name":null,"funder_award_id":"2019B151502001","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285013502.pdf","grobid_xml":"https://content.openalex.org/works/W4285013502.grobid-xml"},"referenced_works_count":86,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W343636949","https://openalex.org/W1980038761","https://openalex.org/W2008056655","https://openalex.org/W2033403400","https://openalex.org/W2054814877","https://openalex.org/W2079057609","https://openalex.org/W2089731186","https://openalex.org/W2117539524","https://openalex.org/W2118858186","https://openalex.org/W2127218421","https://openalex.org/W2130325614","https://openalex.org/W2132377940","https://openalex.org/W2136922672","https://openalex.org/W2156483112","https://openalex.org/W2162833336","https://openalex.org/W2163922914","https://openalex.org/W2167460663","https://openalex.org/W2181347294","https://openalex.org/W2276397252","https://openalex.org/W2308529009","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2515866431","https://openalex.org/W2563711253","https://openalex.org/W2592962403","https://openalex.org/W2593814746","https://openalex.org/W2599837529","https://openalex.org/W2617214882","https://openalex.org/W2626107033","https://openalex.org/W2746791238","https://openalex.org/W2768591600","https://openalex.org/W2769857323","https://openalex.org/W2779692282","https://openalex.org/W2785325870","https://openalex.org/W2798534672","https://openalex.org/W2798680770","https://openalex.org/W2811120218","https://openalex.org/W2901458284","https://openalex.org/W2913939497","https://openalex.org/W2919115771","https://openalex.org/W2924027593","https://openalex.org/W2941964676","https://openalex.org/W2944828972","https://openalex.org/W2950180292","https://openalex.org/W2953469440","https://openalex.org/W2963103975","https://openalex.org/W2963420272","https://openalex.org/W2963465221","https://openalex.org/W2963826423","https://openalex.org/W2964194231","https://openalex.org/W2967065585","https://openalex.org/W2979579363","https://openalex.org/W2986405467","https://openalex.org/W2997574889","https://openalex.org/W3005680577","https://openalex.org/W3034208233","https://openalex.org/W3035160371","https://openalex.org/W3035524453","https://openalex.org/W3105577662","https://openalex.org/W3107045242","https://openalex.org/W3108655343","https://openalex.org/W3110446398","https://openalex.org/W3137513727","https://openalex.org/W3151168706","https://openalex.org/W3175184835","https://openalex.org/W3183873439","https://openalex.org/W3211213470","https://openalex.org/W4210642697","https://openalex.org/W4214644404","https://openalex.org/W4235169531","https://openalex.org/W4244259635","https://openalex.org/W4280648138","https://openalex.org/W4312554651","https://openalex.org/W6678975374","https://openalex.org/W6681096077","https://openalex.org/W6684050148","https://openalex.org/W6684578312","https://openalex.org/W6685380521","https://openalex.org/W6700872662","https://openalex.org/W6701655646","https://openalex.org/W6715501732","https://openalex.org/W6753000030","https://openalex.org/W6759166333","https://openalex.org/W6763442200","https://openalex.org/W6807583345"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2108418243","https://openalex.org/W164103134","https://openalex.org/W2040545019","https://openalex.org/W4391590134","https://openalex.org/W2590770961","https://openalex.org/W3046039077"],"abstract_inverted_index":{"Image":[0],"clustering":[1,36,139],"is":[2,8],"a":[3,41,69,83,113,154],"very":[4],"useful":[5],"technique":[6,130],"that":[7,125,127,163],"widely":[9],"applied":[10,169],"to":[11,58,67,73,92,134,148,170],"various":[12],"areas,":[13],"including":[14],"remote":[15,159,171],"sensing.":[16],"Recently,":[17],"visual":[18],"representations":[19],"by":[20,44],"self-supervised":[21],"learning":[22],"have":[23],"greatly":[24],"improved":[25],"the":[26,34,53,59,65,75,79,87,93,109,117,128,136],"performance":[27,143],"of":[28,89,156],"image":[29,138],"clustering.":[30],"To":[31],"further":[32],"improve":[33,135],"well-trained":[35],"models,":[37,140],"this":[38],"paper":[39],"proposes":[40],"novel":[42],"method":[43,84,152,165],"first":[45],"ranking":[46,66,78],"samples":[47,90],"within":[48],"each":[49],"cluster":[50,61],"based":[51,96],"on":[52,97,153],"confidence":[54],"in":[55,102],"their":[56],"belonging":[57,91],"current":[60,94],"and":[62],"then":[63],"using":[64],"formulate":[68],"weighted":[70],"cross-entropy":[71],"loss":[72],"train":[74],"model.":[76],"For":[77],"samples,":[80],"we":[81,111,161],"developed":[82],"for":[85,107,115],"computing":[86],"likelihood":[88],"clusters":[95],"whether":[98],"they":[99],"are":[100],"situated":[101],"densely":[103],"populated":[104],"neighborhoods,":[105],"while":[106],"training":[108],"model,":[110],"give":[112],"strategy":[114],"weighting":[116],"ranked":[118],"samples.":[119],"We":[120],"present":[121],"extensive":[122],"experimental":[123],"results":[124],"demonstrate":[126],"new":[129],"can":[131,166],"be":[132,167],"used":[133],"state-of-the-art":[137],"achieving":[141],"accuracy":[142],"gains":[144],"ranging":[145],"from":[146,158],"2.1%":[147],"15.9%.":[149],"Performing":[150],"our":[151,164],"variety":[155],"datasets":[157],"sensing,":[160],"show":[162],"effectively":[168],"sensing":[172],"images.":[173]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2022-07-12T00:00:00"}
