{"id":"https://openalex.org/W2808979303","doi":"https://doi.org/10.1109/tnnls.2018.2841009","title":"Self-Paced Learning-Based Probability Subspace Projection for Hyperspectral Image Classification","display_name":"Self-Paced Learning-Based Probability Subspace Projection for Hyperspectral Image Classification","publication_year":2018,"publication_date":"2018-06-21","ids":{"openalex":"https://openalex.org/W2808979303","doi":"https://doi.org/10.1109/tnnls.2018.2841009","mag":"2808979303","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994488"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2018.2841009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2841009","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100764373","display_name":"Shuyuan Yang","orcid":"https://orcid.org/0000-0002-4796-5737"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyuan Yang","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-4796-5737","affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053487344","display_name":"Zhixi Feng","orcid":"https://orcid.org/0000-0002-7372-9180"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixi Feng","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340936","display_name":"Min Wang","orcid":"https://orcid.org/0000-0002-7571-1662"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Wang","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-7571-1662","affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007544409","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0002-9218-5916"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":4.0863,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.94390614,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"30","issue":"2","first_page":"630","last_page":"635"},"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":0.9932000041007996,"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":0.9605000019073486,"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":0.8370835781097412},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7768405675888062},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7257154583930969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.710440993309021},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6744997501373291},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6488060355186462},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6395876407623291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6036019325256348},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5064793825149536},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5045658349990845},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.48003947734832764},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4682534635066986},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.4580598771572113},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3747144937515259},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2898019552230835},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16562828421592712}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8370835781097412},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7768405675888062},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7257154583930969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.710440993309021},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6744997501373291},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6488060355186462},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6395876407623291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6036019325256348},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5064793825149536},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5045658349990845},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.48003947734832764},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4682534635066986},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.4580598771572113},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3747144937515259},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2898019552230835},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16562828421592712},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2018.2841009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2841009","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:29994488","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994488","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2552413355","display_name":null,"funder_award_id":"U1701267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2559168354","display_name":null,"funder_award_id":"91438201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4228412430","display_name":null,"funder_award_id":"61703328","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7555217171","display_name":"\u9690\u7a7a\u95f4\u7a00\u758f\u4e0e\u7ed3\u6784\u5316\u5148\u9a8c\u4e0b\u7684\u975e\u7ebf\u6027\u538b\u7f29\u611f\u77e5\u7814\u7a76","funder_award_id":"61771376","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7595559387","display_name":null,"funder_award_id":"U1730109","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7752695167","display_name":null,"funder_award_id":"91438103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8690032252","display_name":null,"funder_award_id":"61771380","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1799946925","https://openalex.org/W1972693409","https://openalex.org/W2012508386","https://openalex.org/W2019188302","https://openalex.org/W2022631295","https://openalex.org/W2059110141","https://openalex.org/W2063259753","https://openalex.org/W2095832449","https://openalex.org/W2104090753","https://openalex.org/W2105055468","https://openalex.org/W2106777458","https://openalex.org/W2109551918","https://openalex.org/W2117741752","https://openalex.org/W2128194663","https://openalex.org/W2131680909","https://openalex.org/W2132984949","https://openalex.org/W2135343619","https://openalex.org/W2136944379","https://openalex.org/W2138038253","https://openalex.org/W2151599207","https://openalex.org/W2163436471","https://openalex.org/W2171500336","https://openalex.org/W2288723698","https://openalex.org/W2296073425","https://openalex.org/W2316226477","https://openalex.org/W2328735579","https://openalex.org/W2528407067","https://openalex.org/W2574404198","https://openalex.org/W2594785588","https://openalex.org/W2598259734","https://openalex.org/W2619145493","https://openalex.org/W6679390333"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W1637798125","https://openalex.org/W2367926634","https://openalex.org/W2067619203"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"a":[3,18,27,41,46,85],"self-paced":[4,42],"learning-based":[5],"probability":[6,19,47],"subspace":[7],"projection":[8,70],"(SL-PSP)":[9],"method":[10],"is":[11,21,29],"proposed":[12],"for":[13,23,31],"hyperspectral":[14,113],"image":[15],"classification.":[16],"First,":[17],"label":[20,48],"assigned":[22,30],"each":[24,32],"pixel,":[25],"and":[26,45,77,103,124,140],"risk":[28],"labeled":[33,110],"pixel.":[34],"Then,":[35],"two":[36],"regularizers":[37],"are":[38,116],"developed":[39],"from":[40],"maximum":[43],"margin":[44],"graph,":[49],"respectively.":[50],"The":[51,81],"first":[52],"regularizer":[53,83],"can":[54,131],"increase":[55],"the":[56,64,69,98,120,125,133],"discriminant":[57],"ability":[58],"of":[59,92,122,138],"features":[60],"by":[61],"gradually":[62],"involving":[63],"most":[65],"confident":[66],"pixels":[67,102],"into":[68],"to":[71,89,118],"simultaneously":[72],"push":[73],"away":[74],"heterogeneous":[75],"neighbors":[76],"pull":[78],"inhomogeneous":[79],"neighbors.":[80],"second":[82],"adopts":[84],"relaxed":[86],"clustering":[87],"assumption":[88],"make":[90],"avail":[91],"unlabeled":[93],"samples,":[94],"thus":[95],"accurately":[96],"revealing":[97],"affinity":[99],"between":[100],"mixed":[101],"achieving":[104],"accurate":[105],"classification":[106],"with":[107],"very":[108],"few":[109],"samples.":[111],"Several":[112],"data":[114],"sets":[115],"used":[117],"verify":[119],"effectiveness":[121],"SL-PSP,":[123],"experimental":[126],"results":[127,135],"show":[128],"that":[129],"it":[130],"achieve":[132],"state-of-the-art":[134],"in":[136],"terms":[137],"accuracy":[139],"stability.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
