{"id":"https://openalex.org/W4387829008","doi":"https://doi.org/10.1109/igarss52108.2023.10282971","title":"Semi-Supervised Learning for Hyperspectral Images by Non Parametrically Predicting View Assignment<sup>CRediT</sup>","display_name":"Semi-Supervised Learning for Hyperspectral Images by Non Parametrically Predicting View Assignment<sup>CRediT</sup>","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387829008","doi":"https://doi.org/10.1109/igarss52108.2023.10282971"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282971","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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":"https://openalex.org/A5009437784","display_name":"Shivam Pande","orcid":"https://orcid.org/0000-0003-2020-9306"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Shivam Pande","raw_affiliation_strings":["Indian Institute of Technology Bombay,Mumbai,India","Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay,Mumbai,India","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061219999","display_name":"Nassim Ait Ali Braham","orcid":"https://orcid.org/0009-0001-3346-3373"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nassim Ait Ali Braham","raw_affiliation_strings":["German Aerospace Center (DLR),Oberpfaffenhofen,Germany","German Aerospace Center (DLR), Oberpfaffenhofen, Germany"],"affiliations":[{"raw_affiliation_string":"German Aerospace Center (DLR),Oberpfaffenhofen,Germany","institution_ids":["https://openalex.org/I2898391981"]},{"raw_affiliation_string":"German Aerospace Center (DLR), Oberpfaffenhofen, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364938","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-3096-6610"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["German Aerospace Center (DLR),Oberpfaffenhofen,Germany","German Aerospace Center (DLR), Oberpfaffenhofen, Germany"],"affiliations":[{"raw_affiliation_string":"German Aerospace Center (DLR),Oberpfaffenhofen,Germany","institution_ids":["https://openalex.org/I2898391981"]},{"raw_affiliation_string":"German Aerospace Center (DLR), Oberpfaffenhofen, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034296562","display_name":"Conrad M Albrecht","orcid":"https://orcid.org/0009-0009-2422-7289"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Conrad M Albrecht","raw_affiliation_strings":["German Aerospace Center (DLR),Oberpfaffenhofen,Germany","German Aerospace Center (DLR), Oberpfaffenhofen, Germany"],"affiliations":[{"raw_affiliation_string":"German Aerospace Center (DLR),Oberpfaffenhofen,Germany","institution_ids":["https://openalex.org/I2898391981"]},{"raw_affiliation_string":"German Aerospace Center (DLR), Oberpfaffenhofen, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020786167","display_name":"Biplab Banerjee","orcid":"https://orcid.org/0000-0001-8371-8138"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Biplab Banerjee","raw_affiliation_strings":["Indian Institute of Technology Bombay,Mumbai,India","Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay,Mumbai,India","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068384981","display_name":"Xiao Xiang Zhu","orcid":"https://orcid.org/0000-0001-5530-3613"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xiao Xiang Zhu","raw_affiliation_strings":["Technical University of Munich,Munich,Germany","Technical University of Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Munich,Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009437784"],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":0.1621,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5259116,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"6085","last_page":"6088"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9890000224113464,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9818000197410583,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7623016834259033},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.745098352432251},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7131757140159607},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6904153823852539},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6687729358673096},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.6082268953323364},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5842077136039734},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5655326247215271},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5467275381088257},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5428885817527771},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.53717440366745},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4766541123390198},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4751793444156647},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24613195657730103}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7623016834259033},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.745098352432251},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7131757140159607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6904153823852539},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6687729358673096},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.6082268953323364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5842077136039734},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5655326247215271},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5467275381088257},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5428885817527771},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.53717440366745},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4766541123390198},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4751793444156647},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24613195657730103}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282971","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:195498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/IGARSS52108.2023.10282971>.","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1726806267","https://openalex.org/W2757208835","https://openalex.org/W2964137095","https://openalex.org/W2995435108","https://openalex.org/W3158278463","https://openalex.org/W3193557418","https://openalex.org/W4312957058","https://openalex.org/W4312992234","https://openalex.org/W6608394925","https://openalex.org/W6762287338"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W34092691","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2952937263"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"classification":[3],"is":[4],"gaining":[5],"a":[6,36],"lot":[7],"of":[8,14,29,31,80,89,99],"momentum":[9],"in":[10,46,68],"present":[11],"time":[12],"because":[13],"high":[15],"inherent":[16],"spectral":[17],"information":[18],"within":[19],"the":[20,27,53,61,78,85,90,100,108,113,117,143],"images.":[21],"However,":[22],"these":[23],"images":[24],"suffer":[25],"from":[26,116],"problem":[28],"curse":[30],"dimensionality":[32],"and":[33,70,105,136,140,151],"usually":[34],"require":[35],"large":[37],"number":[38],"samples":[39,63,102],"for":[40],"tasks":[41],"such":[42],"as":[43,103],"classification,":[44],"especially":[45],"supervised":[47,152],"setting.":[48,72],"Recently,":[49],"to":[50,83,112],"effectively":[51],"train":[52,121],"deep":[54],"learning":[55,82],"models":[56],"with":[57],"minimal":[58],"labelled":[59,114],"samples,":[60],"unlabeled":[62,101],"are":[64],"also":[65],"being":[66],"leveraged":[67],"self-supervised":[69,87,149],"semi-supervised":[71,81],"In":[73],"this":[74],"work,":[75],"we":[76],"leverage":[77],"idea":[79],"assist":[84],"discriminative":[86],"pretraining":[88],"models.":[91],"The":[92],"proposed":[93,144],"method":[94],"takes":[95],"different":[96],"augmented":[97],"views":[98],"input":[104],"assigns":[106],"them":[107],"same":[109],"pseudo-label":[110],"corresponding":[111],"sample":[115],"downstream":[118],"task.":[119],"We":[120],"our":[122],"model":[123],"on":[124],"two":[125],"HSI":[126],"datasets,":[127],"anemly":[128],"Houston":[129],"dataset":[130],"(from":[131],"data":[132],"fusion":[133],"contest,":[134],"2013)":[135],"Pavia":[137],"university":[138],"dataset,":[139],"show":[141],"that":[142],"approach":[145,150],"performs":[146],"better":[147],"than":[148],"training.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}