{"id":"https://openalex.org/W4379033857","doi":"https://doi.org/10.1109/tgrs.2023.3282048","title":"A Robust Feature Downsampling Module for Remote-Sensing Visual Tasks","display_name":"A Robust Feature Downsampling Module for Remote-Sensing Visual Tasks","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379033857","doi":"https://doi.org/10.1109/tgrs.2023.3282048"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3282048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3282048","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/A5092067348","display_name":"Wei Lu","orcid":"https://orcid.org/0009-0004-5197-5753"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Lu","raw_affiliation_strings":["MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0004-5197-5753","affiliations":[{"raw_affiliation_string":"MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102897927","display_name":"Si-Bao Chen","orcid":"https://orcid.org/0000-0003-1481-0162"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Si-Bao Chen","raw_affiliation_strings":["MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-1481-0162","affiliations":[{"raw_affiliation_string":"MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030720334","display_name":"Jin Tang","orcid":"https://orcid.org/0000-0001-8375-3590"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Tang","raw_affiliation_strings":["MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-8375-3590","affiliations":[{"raw_affiliation_string":"MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102823200","display_name":"Chris Ding","orcid":"https://orcid.org/0009-0009-3374-1941"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chris H. Q. Ding","raw_affiliation_strings":["School of Data Science (SDS), Chinese University of Hong Kong, Shenzhen, China","Presidential Chair Professor at the School of Data Science (SDS) of the Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science (SDS), Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"Presidential Chair Professor at the School of Data Science (SDS) of the Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100372676","display_name":"Bin Luo","orcid":"https://orcid.org/0000-0001-5948-5055"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Luo","raw_affiliation_strings":["MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-5948-5055","affiliations":[{"raw_affiliation_string":"MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2345,"currency":"USD","value_usd":2345},"apc_paid":null,"fwci":9.4186,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.98628293,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","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":0.9998000264167786,"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":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9944999814033508,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9878000020980835,"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/upsampling","display_name":"Upsampling","score":0.9363415241241455},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7756677269935608},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6450285911560059},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6398731470108032},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6121525168418884},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4850963354110718},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.47938087582588196},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.47069764137268066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4389411509037018},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4123595952987671},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1784919798374176}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9363415241241455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7756677269935608},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6450285911560059},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6398731470108032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6121525168418884},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4850963354110718},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47938087582588196},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.47069764137268066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4389411509037018},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4123595952987671},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1784919798374176},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3282048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3282048","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/G2231845458","display_name":null,"funder_award_id":"61860206004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6474056369","display_name":null,"funder_award_id":"61976004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7114861057","display_name":null,"funder_award_id":"U20B2068","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1980038761","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2156303437","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2400138547","https://openalex.org/W2515866431","https://openalex.org/W2592962403","https://openalex.org/W2884822772","https://openalex.org/W2899663614","https://openalex.org/W2908510526","https://openalex.org/W2913314773","https://openalex.org/W2929499422","https://openalex.org/W2946862972","https://openalex.org/W2962749812","https://openalex.org/W2963263347","https://openalex.org/W2964194231","https://openalex.org/W2981662367","https://openalex.org/W2987852271","https://openalex.org/W3034429256","https://openalex.org/W3035682985","https://openalex.org/W3095691842","https://openalex.org/W3105577662","https://openalex.org/W3131500599","https://openalex.org/W3136761610","https://openalex.org/W3138516171","https://openalex.org/W3152083889","https://openalex.org/W3157506437","https://openalex.org/W3168495321","https://openalex.org/W3171087525","https://openalex.org/W3186979696","https://openalex.org/W3194470774","https://openalex.org/W3213288046","https://openalex.org/W3213601271","https://openalex.org/W4214604401","https://openalex.org/W4214648418","https://openalex.org/W4214945166","https://openalex.org/W4225829036","https://openalex.org/W4281664960","https://openalex.org/W4285091717","https://openalex.org/W4285545380","https://openalex.org/W4296544717","https://openalex.org/W4312349930","https://openalex.org/W4312443924","https://openalex.org/W4313007769","https://openalex.org/W4313056180","https://openalex.org/W4313160444","https://openalex.org/W6682864246","https://openalex.org/W6684191040","https://openalex.org/W6726497184","https://openalex.org/W6755977528","https://openalex.org/W6757817989","https://openalex.org/W6758857762","https://openalex.org/W6763251565","https://openalex.org/W6795140394","https://openalex.org/W6796931752","https://openalex.org/W6797578546","https://openalex.org/W6799423381","https://openalex.org/W6842806116"],"related_works":["https://openalex.org/W2060724872","https://openalex.org/W2082094785","https://openalex.org/W2202198356","https://openalex.org/W3087203342","https://openalex.org/W2377184161","https://openalex.org/W228984114","https://openalex.org/W2090026684","https://openalex.org/W4226360758","https://openalex.org/W4212888438","https://openalex.org/W1996690921"],"abstract_inverted_index":{"Remote":[0],"sensing":[1],"(RS)":[2],"images":[3,49],"present":[4],"unique":[5],"challenges":[6],"for":[7,25,44],"computer":[8],"vision":[9],"due":[10],"to":[11,33,127,129,167],"lower":[12],"resolution,":[13],"smaller":[14],"objects,":[15],"and":[16,50,61,106,122,135,151,176,210,215],"fewer":[17],"features.":[18,91],"Mainstream":[19],"backbone":[20],"networks":[21],"show":[22,163],"promising":[23],"results":[24,162,234],"traditional":[26],"visual":[27,247],"tasks.":[28,248],"However,":[29],"they":[30],"use":[31],"convolution":[32],"reduce":[34],"feature":[35,73,84,133,137],"map":[36,85],"dimensionality,":[37],"which":[38],"can":[39],"result":[40],"in":[41,47,103,170,201,208,241],"information":[42],"loss":[43],"small":[45],"objects":[46],"RS":[48,110,158,171,246],"decreased":[51],"performance.":[52],"To":[53],"address":[54],"this":[55,205],"problem,":[56],"we":[57,94],"propose":[58],"a":[59,81,87],"new":[60],"universal":[62],"downsampling":[63,78,142],"module":[64,150,182,220,240],"named":[65],"Robust":[66],"Feature":[67],"Downsampling":[68],"(RFD).":[69],"RFD":[70,117,120,124,149,181,219,239],"fuses":[71],"multiple":[72],"maps":[74],"extracted":[75],"by":[76,225],"different":[77,130],"techniques,":[79],"creating":[80],"more":[82,104],"robust":[83,107],"with":[86,148],"complementary":[88],"set":[89],"of":[90,98,109,116,132,144,188,238,245],"Leveraging":[92],"this,":[93],"overcome":[95],"the":[96,141,222,236,243],"limitations":[97],"conventional":[99],"convolutional":[100],"downsampling,":[101],"resulting":[102,200],"accurate":[105],"analysis":[108],"images.":[111],"We":[112,139],"develop":[113],"two":[114],"versions":[115],"module,":[118],"Shallow":[119],"(SRFD)":[121],"Deep":[123],"(DRFD),":[125],"tailored":[126],"adapt":[128],"stages":[131],"capture":[134],"improve":[136],"robustness.":[138],"replace":[140],"layers":[143],"existing":[145],"mainstream":[146],"backbones":[147],"conduct":[152],"comparative":[153],"experiments":[154],"on":[155,190,204,213],"several":[156],"public":[157],"image":[159,172],"datasets.":[160],"The":[161],"significant":[164],"improvements":[165],"compared":[166],"baseline":[168,223],"approaches":[169,224],"classification,":[173],"object":[174],"detection,":[175],"semantic":[177],"segmentation.":[178],"Specifically,":[179],"our":[180,218],"achieved":[183],"an":[184],"average":[185],"performance":[186,203,244],"gain":[187],"1.5%":[189],"NWPU-RESISC45":[191],"classification":[192],"dataset":[193],"without":[194],"utilizing":[195,228],"any":[196],"additional":[197],"pretraining":[198,229],"data,":[199],"state-of-the-art":[202],"dataset.":[206],"Moreover,":[207],"detection":[209],"segmentation":[211],"tasks":[212],"DOTA":[214],"iSAID":[216],"datasets,":[217],"outperforms":[221],"2-7%":[226],"when":[227],"data":[230],"from":[231],"NWPU-RESISC45.":[232],"These":[233],"highlight":[235],"value":[237],"enhancing":[242]},"counts_by_year":[{"year":2026,"cited_by_count":23},{"year":2025,"cited_by_count":56},{"year":2024,"cited_by_count":12}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
