{"id":"https://openalex.org/W4409991987","doi":"https://doi.org/10.1109/tgrs.2025.3566228","title":"Rethinking Masked Autoencoder for Salient Object Detection in Optical Remote Sensing Images From a Pseudo Image Pretraining Perspective","display_name":"Rethinking Masked Autoencoder for Salient Object Detection in Optical Remote Sensing Images From a Pseudo Image Pretraining Perspective","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409991987","doi":"https://doi.org/10.1109/tgrs.2025.3566228"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3566228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3566228","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/A5003058347","display_name":"Yuxiang Fu","orcid":"https://orcid.org/0009-0003-1811-7274"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxiang Fu","raw_affiliation_strings":["School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086567612","display_name":"Wei Fang","orcid":"https://orcid.org/0000-0002-5561-7249"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Fang","raw_affiliation_strings":["School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051706630","display_name":"Victor S. Sheng","orcid":"https://orcid.org/0000-0003-4960-174X"},"institutions":[{"id":"https://openalex.org/I12315562","display_name":"Texas Tech University","ror":"https://ror.org/0405mnx93","country_code":"US","type":"education","lineage":["https://openalex.org/I12315562"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor S. Sheng","raw_affiliation_strings":["Department of Computer Science, Texas Tech University, Lubbock, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Texas Tech University, Lubbock, TX, USA","institution_ids":["https://openalex.org/I12315562"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003058347"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":2.2743,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.88350892,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9872000217437744,"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":0.9872000217437744,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9800999760627747,"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/autoencoder","display_name":"Autoencoder","score":0.7495747804641724},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7233647704124451},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.7043015956878662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6873054504394531},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6803960204124451},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6081662178039551},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.545201301574707},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.539268970489502},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4422680735588074},{"id":"https://openalex.org/keywords/optical-imaging","display_name":"Optical imaging","score":0.4408014118671417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40690457820892334},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.18834611773490906},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.14177340269088745},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.13384413719177246},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11432650685310364}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7495747804641724},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7233647704124451},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7043015956878662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6873054504394531},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6803960204124451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6081662178039551},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.545201301574707},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.539268970489502},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4422680735588074},{"id":"https://openalex.org/C92630104","wikidata":"https://www.wikidata.org/wiki/Q4115103","display_name":"Optical imaging","level":2,"score":0.4408014118671417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40690457820892334},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.18834611773490906},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.14177340269088745},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.13384413719177246},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11432650685310364}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3566228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3566228","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/G3073828637","display_name":null,"funder_award_id":"No.42475149","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":50,"referenced_works":["https://openalex.org/W1772076007","https://openalex.org/W2323509952","https://openalex.org/W2412782625","https://openalex.org/W2793668851","https://openalex.org/W2807746031","https://openalex.org/W2912465472","https://openalex.org/W2939217524","https://openalex.org/W2967085153","https://openalex.org/W2981374717","https://openalex.org/W2981609437","https://openalex.org/W2990984982","https://openalex.org/W2997316506","https://openalex.org/W2998449272","https://openalex.org/W3010616503","https://openalex.org/W3035422681","https://openalex.org/W3107944836","https://openalex.org/W3108948422","https://openalex.org/W3112885960","https://openalex.org/W3122006940","https://openalex.org/W3132018008","https://openalex.org/W3173382343","https://openalex.org/W3175617055","https://openalex.org/W3188023301","https://openalex.org/W3199185814","https://openalex.org/W3204376324","https://openalex.org/W3208937872","https://openalex.org/W3217306379","https://openalex.org/W4221138999","https://openalex.org/W4223896192","https://openalex.org/W4289752563","https://openalex.org/W4307778795","https://openalex.org/W4312309398","https://openalex.org/W4312820606","https://openalex.org/W4313156423","https://openalex.org/W4313170506","https://openalex.org/W4315631877","https://openalex.org/W4376464584","https://openalex.org/W4384518971","https://openalex.org/W4385444701","https://openalex.org/W4386075861","https://openalex.org/W4386076493","https://openalex.org/W4386083042","https://openalex.org/W4386824701","https://openalex.org/W4388543795","https://openalex.org/W4388624516","https://openalex.org/W4389352387","https://openalex.org/W4392173011","https://openalex.org/W6638992375","https://openalex.org/W6767545893","https://openalex.org/W6839263979"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Recently":[0],"masked":[1,41],"autoencoder":[2],"(MAE)":[3],"has":[4],"achieved":[5],"great":[6],"success":[7],"in":[8,16,30,67,143],"visual":[9],"representation":[10],"learning":[11],"and":[12,64,69,73,133,167,185,206],"delivered":[13],"promising":[14],"potential":[15],"many":[17],"downstream":[18],"vision":[19],"tasks.":[20],"However,":[21],"due":[22],"to":[23,84,97,105,114,156],"the":[24,116,125,159,212,227],"lack":[25],"of":[26,182,198],"saliency":[27,35,65,107,110,121],"supervision":[28,66,111],"signal":[29],"original":[31],"MAE,":[32],"almost":[33],"no":[34],"information":[36,197],"can":[37,50,118],"be":[38],"learned":[39],"from":[40,53,124],"image":[42],"reconstruction":[43],"process.":[44],"Therefore,":[45],"salient":[46,199],"object":[47],"detection":[48],"(SOD)":[49],"hardly":[51],"benefit":[52],"MAE":[54,68,78,91],"pretraining.":[55],"To":[56],"address":[57],"this":[58],"issue,":[59],"we":[60,89,129],"integrate":[61],"SOD":[62,86,103,142],"model":[63,104,117],"propose":[70,130],"a":[71,131],"simple":[72,132],"effective":[74],"framework":[75],"DHMMAE":[76,139],"utilizing":[77],"with":[79],"dynamic":[80],"hybrid":[81],"masking":[82],"ratios":[83],"pretrain":[85],"model.":[87],"Specifically,":[88],"treat":[90],"as":[92],"an":[93],"online":[94],"data":[95],"augmenter":[96],"generate":[98],"endless":[99],"pseudo":[100],"images":[101,147],"for":[102,141,154],"predict":[106],"maps,":[108],"where":[109],"is":[112,231],"employed":[113],"ensure":[115],"learn":[119],"robust":[120],"prior":[122],"knowledge":[123],"reconstructed":[126],"images.":[127],"Besides,":[128],"novel":[134],"network":[135],"EANet":[136,155],"driven":[137],"by":[138,188,201],"pretraining":[140],"optical":[144],"remote":[145],"sensing":[146],"(ORSIs).":[148],"Two":[149],"key":[150],"modules":[151],"are":[152],"designed":[153],"further":[157],"enhance":[158],"performance:":[160],"enhanced":[161],"diverse":[162,176],"feature":[163],"aggregation":[164],"module":[165,172],"(EDFAM)":[166],"adjacent-context":[168],"shuffle":[169,204],"spatial":[170,195,208],"attention":[171,191,209],"(ASSAM).":[173],"EDFAM":[174],"aggregates":[175],"features":[177],"via":[178],"three":[179,218],"different":[180],"types":[181],"convolution":[183,189],"layer":[184],"enhances":[186],"them":[187],"block":[190],"module.":[192],"ASSAM":[193],"captures":[194],"location":[196],"objects":[200],"employing":[202],"channel":[203],"operation":[205],"weighted":[207],"mechanism":[210],"on":[211,217],"fused":[213],"adjacent":[214],"context.":[215],"Experiments":[216],"ORSI-SOD":[219],"datasets":[220],"demonstrate":[221],"that":[222],"our":[223],"proposed":[224],"method":[225],"outperforms":[226],"cutting-edge":[228],"methods.":[229],"Code":[230],"available":[232],"at:":[233],"https://github.com/Voruarn/EANet.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}