{"id":"https://openalex.org/W4409796209","doi":"https://doi.org/10.1109/tgrs.2025.3559224","title":"Temporal-Feedback Self-Training for Semi-Supervised Object Detection in Remote Sensing Images","display_name":"Temporal-Feedback Self-Training for Semi-Supervised Object Detection in Remote Sensing Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409796209","doi":"https://doi.org/10.1109/tgrs.2025.3559224"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3559224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3559224","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":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Temporal-Feedback_Self-Training_for_Semi-Supervised_Object_Detection_in_Remote_Sensing_Images/28743119","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075747444","display_name":"Xiaoqian Zhu","orcid":"https://orcid.org/0000-0002-6709-6604"},"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":"Xiaoqian Zhu","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-6709-6604","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/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":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-0379-2042","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/A5100667596","display_name":"Tianyang Zhang","orcid":"https://orcid.org/0000-0001-9079-7970"},"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":"Tianyang Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-9079-7970","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/A5059262797","display_name":"Xu Tang","orcid":"https://orcid.org/0000-0003-1375-0778"},"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":"Xu Tang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-1375-0778","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/A5039562483","display_name":"Puhua Chen","orcid":"https://orcid.org/0000-0001-5472-1426"},"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":"Puhua Chen","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-5472-1426","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/A5066119228","display_name":"Huiyu Zhou","orcid":"https://orcid.org/0000-0003-1634-9840"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huiyu Zhou","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","School of Computing and Mathematical Sciences, University of Leicester, University Road, Leicester, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-1634-9840","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]},{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, University Road, Leicester, United Kingdom","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"last","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"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10153477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.986299991607666,"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"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.986299991607666,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9754999876022339,"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/T10057","display_name":"Face and Expression Recognition","score":0.9210000038146973,"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/computer-science","display_name":"Computer science","score":0.7044860124588013},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6503046154975891},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6231291890144348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5804702639579773},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5789048075675964},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5339143872261047},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4823876917362213},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32902759313583374},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1141802966594696},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0927373468875885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7044860124588013},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6503046154975891},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6231291890144348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5804702639579773},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5789048075675964},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5339143872261047},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4823876917362213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32902759313583374},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1141802966594696},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0927373468875885},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2025.3559224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3559224","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"},{"id":"pmh:oai:figshare.com:article/28743119","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Temporal-Feedback_Self-Training_for_Semi-Supervised_Object_Detection_in_Remote_Sensing_Images/28743119","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/28743119","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Temporal-Feedback_Self-Training_for_Semi-Supervised_Object_Detection_in_Remote_Sensing_Images/28743119","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1147961060","display_name":null,"funder_award_id":"62276197","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4280920179","display_name":null,"funder_award_id":"2023-CX-TD-09","funder_id":"https://openalex.org/F4320326174","funder_display_name":"Shaanxi Province Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5324547038","display_name":null,"funder_award_id":"62171332","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5584298476","display_name":null,"funder_award_id":"62006178","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/F4320326174","display_name":"Shaanxi Province Postdoctoral Science Foundation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W2017448754","https://openalex.org/W2031489346","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2566079294","https://openalex.org/W2764034829","https://openalex.org/W2800388963","https://openalex.org/W2803867573","https://openalex.org/W2895771689","https://openalex.org/W2935079508","https://openalex.org/W2962749812","https://openalex.org/W2962804657","https://openalex.org/W2991359031","https://openalex.org/W2991363140","https://openalex.org/W2992240579","https://openalex.org/W3024707412","https://openalex.org/W3035160371","https://openalex.org/W3040988483","https://openalex.org/W3109055651","https://openalex.org/W3121842289","https://openalex.org/W3137165785","https://openalex.org/W3158661000","https://openalex.org/W3170602832","https://openalex.org/W3172507542","https://openalex.org/W3174873843","https://openalex.org/W3176748778","https://openalex.org/W3178291178","https://openalex.org/W3180668190","https://openalex.org/W3200975211","https://openalex.org/W3213833596","https://openalex.org/W4207055281","https://openalex.org/W4214648418","https://openalex.org/W4283805107","https://openalex.org/W4285428718","https://openalex.org/W4290715466","https://openalex.org/W4312463868","https://openalex.org/W4312605608","https://openalex.org/W4312711220","https://openalex.org/W4312769060","https://openalex.org/W4312887059","https://openalex.org/W4312999279","https://openalex.org/W4313165093","https://openalex.org/W4383113376","https://openalex.org/W4386075772","https://openalex.org/W4386076234","https://openalex.org/W4386275907","https://openalex.org/W4387918004","https://openalex.org/W6620707391","https://openalex.org/W6717772578","https://openalex.org/W6733814495","https://openalex.org/W6740005241","https://openalex.org/W6766773940","https://openalex.org/W6776700526","https://openalex.org/W6776778719","https://openalex.org/W6788329692","https://openalex.org/W6789505266","https://openalex.org/W6797119129","https://openalex.org/W6802864417","https://openalex.org/W6803687989","https://openalex.org/W6839162681","https://openalex.org/W6849927935"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Although":[0],"modern":[1],"Remote":[2],"Sensing":[3],"Object":[4,38],"Detection":[5,39],"(RSOD)":[6],"methods":[7,48,221],"have":[8],"achieved":[9],"advanced":[10],"performance,":[11,203],"they":[12],"heavily":[13],"rely":[14],"on":[15,42,180],"a":[16,93],"large":[17],"amount":[18],"of":[19,63,105,131,143,170],"annotated":[20],"data.":[21],"This":[22,85,210],"paper":[23,86],"explores":[24],"semi-supervised":[25,101],"RSOD":[26,173],"to":[27,53,58,96,139],"mitigate":[28],"annotation":[29],"costs,":[30],"leveraging":[31],"recent":[32],"extensive":[33,178],"research":[34],"in":[35,51,72,81,100,222],"generic":[36,207,219],"Semi-Supervised":[37],"(SSOD)":[40],"based":[41],"the":[43,59,70,79,88,129,141,146,156,168,171,192,200,205,224],"self-training":[44],"paradigm.":[45],"Current":[46],"SSOD":[47,208,220],"encounter":[49],"challenges":[50,99,225],"adapting":[52],"remote":[54,228],"sensing":[55,229],"images":[56],"due":[57],"complexity":[60],"and":[61,78,115,134,186,195],"variability":[62],"RSIs.":[64],"Two":[65],"key":[66],"issues":[67],"remain":[68],"underexplored:":[69],"noise":[71,124],"pseudo-labels":[73],"caused":[74],"by":[75,127,153,227],"model":[76],"instability":[77],"difficulty":[80],"distinguishing":[82],"similar":[83],"categories.":[84],"introduces":[87],"Temporal-Feedback":[89],"Self-Training":[90],"(TST)":[91],"framework,":[92],"novel":[94],"approach":[95,214],"tackle":[97],"these":[98],"RSOD.":[102],"TST":[103,194],"consists":[104],"two":[106,181],"components:":[107],"Temporal":[108,116],"Consistency":[109],"Based":[110],"Pseudo-labels":[111],"Certainty":[112],"Estimation":[113],"(TCE)":[114],"Self-Feedback":[117],"Feature":[118],"Refinement":[119],"(TSF).":[120],"TCE":[121,196],"addresses":[122],"pseudo-label":[123,132,151],"during":[125,174],"training":[126],"evaluating":[128],"stability":[130],"classification":[133],"localization":[135],"over":[136],"time":[137],"series":[138],"assess":[140],"quality":[142,152],"pseudo-labels.":[144],"On":[145],"other":[147],"hand,":[148],"TSF":[149],"enhances":[150],"dynamically":[154],"identifying":[155],"models":[157,202],"confusing":[158],"categories":[159],"as":[160],"feedback":[161],"for":[162],"feature":[163],"refinement.":[164],"Both":[165],"components":[166,197],"facilitate":[167],"progression":[169],"self-training-based":[172],"training.":[175],"We":[176],"conducted":[177],"experiments":[179],"challenging":[182],"public":[183],"datasets,":[184],"DOTA":[185],"DIOR.":[187],"The":[188],"results":[189],"demonstrate":[190],"that":[191,212],"proposed":[193],"significantly":[198],"improve":[199],"baseline":[201],"surpassing":[204],"state-of-the-art":[206],"method.":[209],"suggests":[211],"our":[213],"is":[215],"more":[216],"effective":[217],"than":[218],"addressing":[223],"posed":[226],"images.":[230]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
