{"id":"https://openalex.org/W4404788913","doi":"https://doi.org/10.1109/tgrs.2024.3507385","title":"DAE-GSP: Discriminative Autoencoder With Gaussian Selective Patch for Multimodal Remote Sensing Image Classification","display_name":"DAE-GSP: Discriminative Autoencoder With Gaussian Selective Patch for Multimodal Remote Sensing Image Classification","publication_year":2024,"publication_date":"2024-11-27","ids":{"openalex":"https://openalex.org/W4404788913","doi":"https://doi.org/10.1109/tgrs.2024.3507385"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3507385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3507385","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/A5024219043","display_name":"M. Li","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":"Mengchang Li","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;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":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-7372-9180","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","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":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-4796-5737","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114911363","display_name":"Yue Ma","orcid":"https://orcid.org/0000-0002-5422-315X"},"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":"Yue Ma","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-5422-315X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043575604","display_name":"Liangliang Song","orcid":"https://orcid.org/0000-0002-2187-727X"},"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":"Liangliang Song","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-2187-727X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396684","display_name":"Shuai Chen","orcid":"https://orcid.org/0000-0002-8293-7491"},"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":"Shuai Chen","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":"https://orcid.org/0000-0003-3354-9617"},"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":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-3354-9617","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026460845","display_name":"Junkai Zhang","orcid":"https://orcid.org/0000-0002-6407-6173"},"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":"Junkai Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;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":0.8135,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77429855,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.859000027179718,"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":0.859000027179718,"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":0.8277999758720398,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.7631999850273132,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/discriminative-model","display_name":"Discriminative model","score":0.6818138360977173},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.678426206111908},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6546008586883545},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5502156019210815},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5242667198181152},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5172232389450073},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5133096575737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.504925549030304},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4741860330104828},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4634629786014557},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4087477922439575},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3239631950855255},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2713031768798828},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10832399129867554},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.08497276902198792}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6818138360977173},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.678426206111908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6546008586883545},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5502156019210815},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5242667198181152},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5172232389450073},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5133096575737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.504925549030304},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4741860330104828},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4634629786014557},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4087477922439575},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3239631950855255},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2713031768798828},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10832399129867554},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.08497276902198792},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3507385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3507385","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G1560732540","display_name":null,"funder_award_id":"62276205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5111323382","display_name":null,"funder_award_id":"61906145","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5498747354","display_name":null,"funder_award_id":"U22B2018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6735595969","display_name":null,"funder_award_id":"XJSJ24069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6986719856","display_name":null,"funder_award_id":"62171357","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1974689592","https://openalex.org/W2029992428","https://openalex.org/W2104896032","https://openalex.org/W2111809230","https://openalex.org/W2171590421","https://openalex.org/W2623518586","https://openalex.org/W2799390666","https://openalex.org/W2842511635","https://openalex.org/W2890133123","https://openalex.org/W2908349615","https://openalex.org/W2945177640","https://openalex.org/W2945608588","https://openalex.org/W2955671895","https://openalex.org/W2983376237","https://openalex.org/W2997591727","https://openalex.org/W2998002262","https://openalex.org/W2999585470","https://openalex.org/W3026303927","https://openalex.org/W3133271982","https://openalex.org/W3151168706","https://openalex.org/W3168367808","https://openalex.org/W3174415835","https://openalex.org/W4205601058","https://openalex.org/W4206025940","https://openalex.org/W4206522033","https://openalex.org/W4220840497","https://openalex.org/W4280490589","https://openalex.org/W4285228203","https://openalex.org/W4288391270","https://openalex.org/W4294068600","https://openalex.org/W4312336012","https://openalex.org/W4312592451","https://openalex.org/W4312981890","https://openalex.org/W4313156423","https://openalex.org/W4313555745","https://openalex.org/W4315606133","https://openalex.org/W4321483963","https://openalex.org/W4362014056","https://openalex.org/W4372346621","https://openalex.org/W4379984088","https://openalex.org/W4382998925","https://openalex.org/W4382999123","https://openalex.org/W4384161871","https://openalex.org/W4384915783","https://openalex.org/W4385245566","https://openalex.org/W4385579446","https://openalex.org/W4388543795","https://openalex.org/W4389104669","https://openalex.org/W4389778595","https://openalex.org/W4390480870","https://openalex.org/W4390873136","https://openalex.org/W4391935886","https://openalex.org/W4392566508","https://openalex.org/W4392796571","https://openalex.org/W4393153184","https://openalex.org/W4394606408","https://openalex.org/W4399074152","https://openalex.org/W6755207826","https://openalex.org/W6757817989","https://openalex.org/W6776700526","https://openalex.org/W6779992872","https://openalex.org/W6791353385","https://openalex.org/W6838673894","https://openalex.org/W6858621262"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2761785940","https://openalex.org/W2129933262"],"abstract_inverted_index":{"In":[0,45,112],"the":[1,72,107,124,140,148,167,170,181,194],"field":[2],"of":[3,82,109,126,143,169,188,203],"multimodal":[4],"remote":[5],"sensing":[6],"image":[7,74],"(MRSI)":[8],"classification,":[9],"self-supervised":[10,134],"learning":[11,70,81],"(SSL)":[12],"algorithms":[13],"have":[14],"demonstrated":[15],"significant":[16],"advantages,":[17],"particularly":[18],"in":[19],"scenarios":[20],"with":[21,57,71,133],"limited":[22],"labeled":[23,176],"samples.":[24],"Existing":[25],"SSL":[26,53],"methods":[27],"typically":[28],"use":[29],"auxiliary":[30,135],"tasks":[31],"within":[32],"either":[33],"contrastive":[34,69],"or":[35,41],"generative":[36],"frameworks,":[37],"focusing":[38],"on":[39,158,193],"discriminative":[40,55,86],"structural":[42,83],"information":[43,84],"separately.":[44],"this":[46,137],"article,":[47],"we":[48,114],"propose":[49,115],"a":[50,91,116],"novel":[51,117],"hybrid":[52],"paradigm,":[54],"autoencoder":[56],"Gaussian":[58,118],"selective":[59,119],"patch":[60,120,129],"(DAE-GSP)":[61],"for":[62,79],"MRSI":[63],"classification.":[64],"The":[65],"DAE":[66],"framework":[67],"integrates":[68],"masked":[73],"modeling":[75],"(MIM)":[76],"technique,":[77],"allowing":[78],"simultaneous":[80],"and":[85,146,164,191,197,206],"representations":[87],"from":[88],"images.":[89],"Furthermore,":[90],"cross-attention-based":[92],"data-level":[93],"fusion":[94],"strategy":[95,138],"is":[96],"introduced":[97],"during":[98],"pretraining":[99],"stage":[100],"to":[101,150],"enhance":[102],"intermodal":[103],"interactions,":[104],"thereby":[105],"improving":[106],"effectiveness":[108,168],"modality":[110],"fusion.":[111],"addition,":[113],"(GSP)":[121],"strategy,":[122],"addressing":[123],"limitations":[125],"traditional":[127],"square":[128],"selection":[130],"methods.":[131,210],"Combined":[132],"tasks,":[136],"facilitates":[139],"improved":[141],"integration":[142],"multiple":[144],"modalities":[145],"encourages":[147],"model":[149],"capture":[151],"essential":[152],"semantic":[153],"information.":[154],"Extensive":[155],"experiments":[156],"conducted":[157],"three":[159],"public":[160],"datasets":[161],"(Houston2013,":[162],"Augsburg,":[163,196],"Berlin)":[165],"demonstrate":[166],"proposed":[171,182],"approach.":[172],"With":[173],"only":[174],"ten":[175],"training":[177],"samples":[178],"per":[179],"class,":[180],"method":[183],"achieves":[184],"overall":[185],"accuracy":[186],"(OA)":[187],"90.15%,":[189],"82.64%,":[190],"71.03%":[192],"Houston2013,":[195],"Berlin":[198],"datasets,":[199],"respectively,":[200],"indicating":[201],"improvements":[202],"1.31%,":[204],"1.22%,":[205],"1.48%":[207],"over":[208],"state-of-the-art":[209]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
