{"id":"https://openalex.org/W3206999444","doi":"https://doi.org/10.1109/igarss47720.2021.9554202","title":"Semi-Supervised Object Detection Framework with Object First Mixup for Remote Sensing Images","display_name":"Semi-Supervised Object Detection Framework with Object First Mixup for Remote Sensing Images","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3206999444","doi":"https://doi.org/10.1109/igarss47720.2021.9554202","mag":"3206999444"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9554202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101849792","display_name":"Ziyu Zhang","orcid":"https://orcid.org/0000-0002-5625-4726"},"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":"Ziyu Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'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'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","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'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'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":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2596","last_page":"2599"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9986000061035156,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9979000091552734,"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":0.790634036064148},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7191417813301086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6732560396194458},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6654863357543945},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.659957766532898},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6416248083114624},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5009398460388184},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4904310405254364},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4832497239112854},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42508238554000854}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.790634036064148},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7191417813301086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6732560396194458},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6654863357543945},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.659957766532898},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6416248083114624},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5009398460388184},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4904310405254364},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4832497239112854},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42508238554000854},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/igarss47720.2021.9554202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2577537809","https://openalex.org/W2765407302","https://openalex.org/W3021542222","https://openalex.org/W6745136726","https://openalex.org/W6776778719"],"related_works":["https://openalex.org/W1603736412","https://openalex.org/W4304185162","https://openalex.org/W2061685118","https://openalex.org/W3006282800","https://openalex.org/W2462100143","https://openalex.org/W1770503332","https://openalex.org/W3125207769","https://openalex.org/W2577825108","https://openalex.org/W2949684406","https://openalex.org/W4299904075"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3],"Simple":[4],"Semi-supervised":[5],"Object":[6,39],"Detection":[7],"framework":[8],"for":[9],"Remote":[10],"Sensing":[11],"images,":[12],"which":[13,54],"is":[14,43,86],"named":[15],"SSOD-RS.":[16],"SSOD-RS":[17,112],"contains":[18],"two":[19],"parts,":[20],"improved":[21,32],"self-training":[22,89],"and":[23,51,84],"consistency":[24],"regularization":[25],"based":[26],"on":[27],"strong":[28],"data":[29],"augmentations":[30],"with":[31,81],"mixup.":[33],"Firstly,":[34],"as":[35],"an":[36],"augmentation":[37],"algorithm,":[38],"First":[40],"mixup":[41],"(OF-mixup)":[42],"proposed":[44],"to":[45,71,90],"adjust":[46],"the":[47,52,56,63,66,72,77,92,95,99,103,106,121,124],"weight":[48],"of":[49,58,65,74,79,98,115,123],"objects":[50],"background,":[53],"expands":[55],"distribution":[57,97],"training":[59,80],"samples":[60],"while":[61],"reducing":[62],"interference":[64],"remote":[67],"sensing":[68],"complex":[69],"background":[70],"features":[73,104],"objects.":[75],"Secondly,":[76],"strategy":[78],"assembling":[82],"loss":[83],"fine-tuning":[85],"introduced":[87],"into":[88],"make":[91],"model":[93],"fit":[94],"feature":[96],"true-labels":[100],"after":[101],"learning":[102],"from":[105],"pseudo-labels.":[107],"Experimental":[108],"results":[109],"demonstrate":[110],"that":[111],"making":[113],"use":[114],"unlabeled":[116],"images":[117],"can":[118],"significantly":[119],"improve":[120],"accuracy":[122],"model.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}