{"id":"https://openalex.org/W2884965832","doi":"https://doi.org/10.1109/jstars.2018.2854893","title":"Marginal Stacked Autoencoder With Adaptively-Spatial Regularization for Hyperspectral Image Classification","display_name":"Marginal Stacked Autoencoder With Adaptively-Spatial Regularization for Hyperspectral Image Classification","publication_year":2018,"publication_date":"2018-07-26","ids":{"openalex":"https://openalex.org/W2884965832","doi":"https://doi.org/10.1109/jstars.2018.2854893","mag":"2884965832"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2018.2854893","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2854893","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5045546082","display_name":"Jie Feng","orcid":"https://orcid.org/0000-0002-8032-7542"},"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":true,"raw_author_name":"Jie Feng","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-8032-7542","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053587654","display_name":"Liguo Liu","orcid":"https://orcid.org/0000-0002-6064-8701"},"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":"Liguo Liu","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100681906","display_name":"Xianghai Cao","orcid":"https://orcid.org/0000-0003-0997-4664"},"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":"Xianghai Cao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-0997-4664","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":null},"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":"Licheng Jiao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106406829","display_name":"Tao Sun","orcid":"https://orcid.org/0000-0002-6618-1081"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Sun","raw_affiliation_strings":["Huawei Technologies Co. Ltd., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd., Xi'an, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049776440","display_name":"Xiangrong Zhang","orcid":"https://orcid.org/0000-0003-0379-2042"},"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":"Xiangrong Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-0379-2042","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5045546082"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":3.3459,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.93225164,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"9","first_page":"3297","last_page":"3311"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.991100013256073,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9878000020980835,"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":0.859764814376831},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7762226462364197},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.698494553565979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6947063207626343},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6894046068191528},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6886845827102661},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6092149615287781},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5445830821990967},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4815159738063812},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43722668290138245},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4265858829021454},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4217027723789215},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3885502815246582},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2758738398551941},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.196563720703125}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.859764814376831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7762226462364197},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.698494553565979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6947063207626343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894046068191528},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6886845827102661},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6092149615287781},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5445830821990967},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4815159738063812},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43722668290138245},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4265858829021454},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4217027723789215},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3885502815246582},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2758738398551941},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.196563720703125}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2018.2854893","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2854893","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2743047296","display_name":null,"funder_award_id":"61573267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4311743635","display_name":null,"funder_award_id":"2016T90892","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G4393970417","display_name":null,"funder_award_id":"JBX181707","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4420409375","display_name":null,"funder_award_id":"LSIT201803D","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G6484524917","display_name":null,"funder_award_id":"2015M570816","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6915461351","display_name":null,"funder_award_id":"61502369","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7442798324","display_name":null,"funder_award_id":"61501353","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"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1484785429","https://openalex.org/W1590946397","https://openalex.org/W1836465849","https://openalex.org/W1881043346","https://openalex.org/W1990895816","https://openalex.org/W1992961908","https://openalex.org/W2000563363","https://openalex.org/W2000649470","https://openalex.org/W2001141328","https://openalex.org/W2029316659","https://openalex.org/W2039409148","https://openalex.org/W2042576467","https://openalex.org/W2043945532","https://openalex.org/W2044184146","https://openalex.org/W2044439250","https://openalex.org/W2064987453","https://openalex.org/W2066724243","https://openalex.org/W2072599882","https://openalex.org/W2076063813","https://openalex.org/W2090424610","https://openalex.org/W2097900616","https://openalex.org/W2097940622","https://openalex.org/W2098057602","https://openalex.org/W2100285320","https://openalex.org/W2100495367","https://openalex.org/W2113464037","https://openalex.org/W2117633874","https://openalex.org/W2118246710","https://openalex.org/W2135431554","https://openalex.org/W2136251662","https://openalex.org/W2138857742","https://openalex.org/W2145094598","https://openalex.org/W2146952738","https://openalex.org/W2148713643","https://openalex.org/W2151288205","https://openalex.org/W2151599207","https://openalex.org/W2171350553","https://openalex.org/W2219715551","https://openalex.org/W2275445006","https://openalex.org/W2337945445","https://openalex.org/W2344138609","https://openalex.org/W2494485523","https://openalex.org/W2506684654","https://openalex.org/W2519653196","https://openalex.org/W2527419569","https://openalex.org/W2546696642","https://openalex.org/W2548476632","https://openalex.org/W2548791488","https://openalex.org/W2562461367","https://openalex.org/W2567582497","https://openalex.org/W2592141703","https://openalex.org/W2598997103","https://openalex.org/W2765739551","https://openalex.org/W2997574889","https://openalex.org/W3148981562","https://openalex.org/W6638667902","https://openalex.org/W6680300913","https://openalex.org/W6681096077"],"related_works":["https://openalex.org/W2146886779","https://openalex.org/W3160263555","https://openalex.org/W4287995534","https://openalex.org/W2998168123","https://openalex.org/W2897995864","https://openalex.org/W2292254049","https://openalex.org/W3173596272","https://openalex.org/W2742991909","https://openalex.org/W3105255022","https://openalex.org/W2767651786"],"abstract_inverted_index":{"Stacked":[0],"autoencoder":[1],"(SAE)":[2],"provides":[3,169],"excellent":[4],"performance":[5,172],"for":[6,54],"image":[7,56,68],"processing":[8],"under":[9],"sufficient":[10],"training":[11,17,25,105,139],"samples.":[12,106,140],"However,":[13],"the":[14,33,67,75,91,102,108,111,122,132,142,152,156,166],"collection":[15],"of":[16,35,88,104,144],"samples":[18,26,89,99,113,153],"is":[19,52,63,82,148],"difficult":[20],"in":[21,90,155],"hyperspectral":[22,55,163],"images.":[23,39],"Insufficient":[24],"easily":[27],"make":[28],"SAE":[29,36,47],"overfit":[30],"and":[31],"limit":[32],"application":[34],"to":[37,65,84,100,120,130],"hypersepctral":[38],"To":[40],"address":[41],"this":[42],"problem,":[43],"a":[44,59],"novel":[45],"marginal":[46,112],"with":[48,174],"adaptively-spatial":[49],"regularization":[50,81],"(ARMSAE)":[51],"proposed":[53,167],"classification.":[57],"First,":[58],"superpixel":[60],"segmentation":[61],"method":[62,168],"used":[64],"divide":[66],"into":[69],"many":[70],"homogenous":[71,92,158],"regions.":[72,93],"Then,":[73],"at":[74],"pretraining":[76],"stage,":[77,110],"an":[78],"adaptively-shaped":[79],"spatial":[80],"introduced":[83],"extract":[85],"contextual":[86],"information":[87],"It":[94],"sufficiently":[95],"utilizes":[96],"unlabeled":[97],"adjacent":[98],"alleviate":[101,131],"lack":[103],"At":[107],"fine-tuning":[109,126],"based":[114],"on":[115,162],"geometrical":[116],"property":[117],"are":[118],"selected":[119],"tune":[121],"ARMSAE":[123],"network.":[124],"The":[125],"exploits":[127],"margin":[128],"strategy":[129],"inaccurate":[133],"statistical":[134],"estimation":[135],"caused":[136],"by":[137,150],"insufficient":[138],"Finally,":[141],"label":[143],"each":[145],"test":[146],"sample":[147],"determined":[149],"all":[151],"locating":[154],"same":[157],"region.":[159],"Experimental":[160],"results":[161],"images":[164],"demonstrate":[165],"encouraging":[170],"classification":[171],"compared":[173],"several":[175],"related":[176],"state-of-the-art":[177],"methods.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
