{"id":"https://openalex.org/W2806437580","doi":"https://doi.org/10.1109/tgrs.2018.2837142","title":"Hyperspectral Image Classification Based on Deep Deconvolution Network With Skip Architecture","display_name":"Hyperspectral Image Classification Based on Deep Deconvolution Network With Skip Architecture","publication_year":2018,"publication_date":"2018-06-05","ids":{"openalex":"https://openalex.org/W2806437580","doi":"https://doi.org/10.1109/tgrs.2018.2837142","mag":"2806437580"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2837142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2837142","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-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/A5087248518","display_name":"Xiaorui Ma","orcid":"https://orcid.org/0000-0001-7697-2285"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaorui Ma","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-7697-2285","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083720313","display_name":"Anyan Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anyan Fu","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440164","display_name":"Jie Wang","orcid":"https://orcid.org/0000-0003-1172-1551"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["School of Information Science and Technology, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0003-1172-1551","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422639","display_name":"Hongyu Wang","orcid":"https://orcid.org/0000-0002-1038-412X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Wang","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-1038-412X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020527092","display_name":"Baocai Yin","orcid":"https://orcid.org/0000-0003-3121-1823"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baocai Yin","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.8071,"has_fulltext":false,"cited_by_count":81,"citation_normalized_percentile":{"value":0.98278076,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"56","issue":"8","first_page":"4781","last_page":"4791"},"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":0.9951000213623047,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9564999938011169,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8225891590118408},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.8074935674667358},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7570633888244629},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7296733260154724},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7140656113624573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.702017605304718},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6147427558898926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6100776195526123},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5433900356292725},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5231450796127319},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.512108325958252},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49073541164398193},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4380486309528351},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4325520992279053},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.43243199586868286},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4186946153640747},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3666278123855591},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.35584113001823425},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3332563042640686},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20747774839401245},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0841609537601471}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8225891590118408},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.8074935674667358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7570633888244629},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7296733260154724},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7140656113624573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.702017605304718},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6147427558898926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6100776195526123},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5433900356292725},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5231450796127319},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.512108325958252},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49073541164398193},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4380486309528351},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4325520992279053},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.43243199586868286},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4186946153640747},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3666278123855591},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35584113001823425},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3332563042640686},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20747774839401245},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0841609537601471},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2018.2837142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2837142","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1500189215","display_name":"\u9ad8\u5149\u8c31\u4e0e\u6781\u5316SAR\u56fe\u50cf\u534f\u540c\u6df1\u5ea6\u5b66\u4e60\u5206\u7c7b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61671103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1655372983","display_name":null,"funder_award_id":"DUT17RC(3)024","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4459139658","display_name":null,"funder_award_id":"3132016318","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4892834641","display_name":"\u57fa\u4e8e\u591a\u57df\u5c04\u9891\u5c42\u6790\u6210\u50cf\u7684\u88ab\u52a8\u65e0\u7ebf\u5b9a\u4f4d\u4e0e\u72b6\u6001\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61671102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5826463664","display_name":null,"funder_award_id":"2018M630288","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6206345682","display_name":null,"funder_award_id":"ICT1800378","funder_id":"https://openalex.org/F4320322927","funder_display_name":"Zhejiang University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322874","display_name":"Universit\u00e0 degli Studi di Pavia","ror":"https://ror.org/00s6t1f81"},{"id":"https://openalex.org/F4320322927","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884"},{"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":45,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1843779453","https://openalex.org/W1920235975","https://openalex.org/W1997565609","https://openalex.org/W1997718749","https://openalex.org/W2008847349","https://openalex.org/W2029316659","https://openalex.org/W2136251662","https://openalex.org/W2179290474","https://openalex.org/W2342611082","https://openalex.org/W2342652911","https://openalex.org/W2342880667","https://openalex.org/W2358876993","https://openalex.org/W2500751094","https://openalex.org/W2512351403","https://openalex.org/W2540935574","https://openalex.org/W2548791488","https://openalex.org/W2558391528","https://openalex.org/W2587790406","https://openalex.org/W2592224809","https://openalex.org/W2598259734","https://openalex.org/W2603422184","https://openalex.org/W2603834682","https://openalex.org/W2605793178","https://openalex.org/W2607476064","https://openalex.org/W2611655888","https://openalex.org/W2613557745","https://openalex.org/W2614256707","https://openalex.org/W2614326984","https://openalex.org/W2616976651","https://openalex.org/W2732412926","https://openalex.org/W2743255627","https://openalex.org/W2744582969","https://openalex.org/W2754507318","https://openalex.org/W2767340384","https://openalex.org/W2767805377","https://openalex.org/W2768537477","https://openalex.org/W2779335303","https://openalex.org/W2782517596","https://openalex.org/W2782522152","https://openalex.org/W2783165089","https://openalex.org/W2783231089","https://openalex.org/W2919115771","https://openalex.org/W2963377935","https://openalex.org/W3103753223"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W2150029999","https://openalex.org/W2107493002"],"abstract_inverted_index":{"Convolution":[0],"neural":[1],"network":[2,82,93,168],"(CNN)":[3],"utilizes":[4],"alternating":[5],"convolutional":[6],"and":[7,44,102,118,124,138,144],"pooling":[8,42,136],"layers":[9,137],"to":[10,86,115,129],"learn":[11,87,139],"representative":[12],"spatial":[13,100,107,141],"information":[14,30,39,47,133,155],"when":[15],"the":[16,37,41,45,52,73,88,99,106,120,131,135,145,152,157,162,184,188],"training":[17,55],"samples":[18,56],"are":[19,127],"sufficient.":[20],"However,":[21],"for":[22,150,171],"pixelwise":[23,140],"classification":[24],"of":[25,54,134,187],"hyperspectral":[26],"image,":[27],"some":[28],"important":[29],"is":[31,57,113,148,169],"neglected":[32],"by":[33,40],"CNN,":[34],"such":[35],"as":[36],"erased":[38,132],"operation":[43],"appearance":[46,159],"from":[48],"lower":[49],"layers.":[50],"Moreover,":[51],"lack":[53],"a":[58,109,165],"common":[59],"situation":[60],"in":[61],"remote":[62],"sensing":[63],"area,":[64],"which":[65],"afflicts":[66],"CNN":[67],"with":[68,83,95,156],"overfitting":[69,121],"problem.":[70],"To":[71],"address":[72],"aforementioned":[74],"issues,":[75],"this":[76],"paper":[77],"designs":[78],"an":[79],"end-to-end":[80],"deconvolution":[81,125],"skip":[84,146],"architecture":[85,147],"spectral-spatial":[89],"features.":[90,175],"The":[91],"proposed":[92,189],"starts":[94],"two":[96],"branches,":[97],"i.e.,":[98],"branch":[101],"spectral":[103,163,174],"branch.":[104],"In":[105,161],"branch,":[108,164],"band":[110],"selection":[111],"layer":[112],"designed":[114],"reduce":[116],"parameters":[117],"remit":[119],"problem,":[122],"unpooling":[123],"operations":[126],"utilized":[128],"recover":[130],"representation":[142],"hierarchically,":[143],"constructed":[149],"merging":[151],"deep":[153,167,173],"semantic":[154],"shallow":[158],"information.":[160],"contextual":[166],"employed":[170],"learning":[172],"Experimental":[176],"results":[177],"on":[178],"three":[179],"benchmark":[180],"data":[181],"sets":[182],"reveal":[183],"competitive":[185],"performance":[186],"approach":[190],"over":[191],"several":[192],"related":[193],"methods.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}