{"id":"https://openalex.org/W4387829473","doi":"https://doi.org/10.1109/igarss52108.2023.10282253","title":"Semi-Supervised Classification of Hyperspectral Images based on Contrastive Learning Constraint","display_name":"Semi-Supervised Classification of Hyperspectral Images based on Contrastive Learning Constraint","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387829473","doi":"https://doi.org/10.1109/igarss52108.2023.10282253"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10282253","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/A5102570123","display_name":"Junyuan Ding","orcid":"https://orcid.org/0009-0001-4959-3762"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyuan Ding","raw_affiliation_strings":["Northwestern Polytechnical University,School of Cyberspace Security,Xi’an,China,710072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Cyberspace Security,Xi’an,China,710072","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101681708","display_name":"Yue Wen","orcid":"https://orcid.org/0000-0001-5297-6230"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Wen","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070266422","display_name":"Wei\u2010Xin Ren","orcid":"https://orcid.org/0000-0003-0314-0407"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixin Ren","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100687346","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0001-6499-5711"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100323672","display_name":"Wei Wei","orcid":"https://orcid.org/0000-0002-0655-056X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wei","raw_affiliation_strings":["Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072","Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Computer Science,Xi’an,China,710072","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.2976,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61745595,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"7273","last_page":"7276"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9930999875068665,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9800000190734863,"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":0.7939040064811707},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7739248275756836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7364946007728577},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.705581784248352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6742218732833862},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6496126651763916},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.624172031879425},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49776625633239746},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4807436466217041},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4796088933944702},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4498339593410492},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4308062195777893},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30351144075393677},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.30215880274772644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1561327576637268}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7939040064811707},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7739248275756836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7364946007728577},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.705581784248352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6742218732833862},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6496126651763916},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.624172031879425},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49776625633239746},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4807436466217041},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4796088933944702},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4498339593410492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4308062195777893},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30351144075393677},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30215880274772644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1561327576637268},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10282253","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2008509935","https://openalex.org/W2136132422","https://openalex.org/W2136251662","https://openalex.org/W2500751094","https://openalex.org/W2620547787","https://openalex.org/W2909158354","https://openalex.org/W2915851545","https://openalex.org/W2940678725","https://openalex.org/W4318483117"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Despite":[0],"significant":[1],"advancements":[2],"in":[3],"deep":[4],"learning-based":[5],"algorithms":[6],"for":[7],"classifying":[8],"hyperspectral":[9],"image":[10],"(HSI),":[11],"this":[12,25],"task":[13],"remains":[14],"challenging":[15],"when":[16],"only":[17],"few":[18],"labeled":[19,57,94],"training":[20],"examples":[21],"are":[22],"available.":[23],"In":[24],"paper,":[26],"we":[27,76],"introduce":[28],"a":[29,35,43,53,61,78],"contrastive":[30,70,79],"learning":[31],"constraint":[32],"and":[33,96],"propose":[34],"semi-supervised":[36,113],"HSI":[37,88,114],"classification":[38,89,115],"approach.":[39],"We":[40],"first":[41],"build":[42],"multi-scale":[44],"feature":[45],"extraction":[46],"module,":[47,81],"which":[48,82],"extracts":[49],"fine-grained":[50],"features":[51],"from":[52],"small":[54],"number":[55],"of":[56,64,110],"samples":[58],"together":[59],"with":[60],"huge":[62],"amount":[63],"unlabeled":[65,74],"samples.":[66],"Then,":[67],"by":[68],"modeling":[69],"constraints":[71],"on":[72,92,104],"the":[73,86,93,99,108,111],"data,":[75],"construct":[77],"sub-network":[80,90],"can":[83],"efficiently":[84],"support":[85],"supervised":[87],"trained":[91],"dataset":[95],"hence":[97],"enhance":[98],"generalization":[100],"ability.":[101],"Experimental":[102],"results":[103],"two":[105],"datasets":[106],"demonstrate":[107],"effectiveness":[109],"proposed":[112],"methods.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}