{"id":"https://openalex.org/W4319019665","doi":"https://doi.org/10.3390/rs15030827","title":"A Review of Data Augmentation Methods of Remote Sensing Image Target Recognition","display_name":"A Review of Data Augmentation Methods of Remote Sensing Image Target Recognition","publication_year":2023,"publication_date":"2023-02-01","ids":{"openalex":"https://openalex.org/W4319019665","doi":"https://doi.org/10.3390/rs15030827"},"language":"en","primary_location":{"id":"doi:10.3390/rs15030827","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030827","pdf_url":"https://www.mdpi.com/2072-4292/15/3/827/pdf?version=1675916543","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"review","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/3/827/pdf?version=1675916543","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020997418","display_name":"Xuejie Hao","orcid":"https://orcid.org/0000-0003-1288-6155"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuejie Hao","raw_affiliation_strings":["College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China"],"affiliations":[{"raw_affiliation_string":"College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396529","display_name":"Lu Liu","orcid":"https://orcid.org/0000-0003-0996-3017"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Liu","raw_affiliation_strings":["College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China"],"affiliations":[{"raw_affiliation_string":"College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033393950","display_name":"Rongjin Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156332","display_name":"Chinese Research Academy of Environmental Sciences","ror":"https://ror.org/05t8xvx87","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210156332"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongjin Yang","raw_affiliation_strings":["Chinese Research Academy of Environmental Sciences, No. 8, Da Yang Fang, An Wai, Chao Yang District, Beijing 100012, China"],"affiliations":[{"raw_affiliation_string":"Chinese Research Academy of Environmental Sciences, No. 8, Da Yang Fang, An Wai, Chao Yang District, Beijing 100012, China","institution_ids":["https://openalex.org/I4210156332"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089296080","display_name":"Lizeyan Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I198244214","display_name":"Universit\u00e9 Clermont Auvergne","ror":"https://ror.org/01a8ajp46","country_code":"FR","type":"education","lineage":["https://openalex.org/I198244214"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lizeyan Yin","raw_affiliation_strings":["Institute of Computing, Modeling and Their Applications, Clermont-Auvergne University, 63000 Clermont-Ferrand, France"],"affiliations":[{"raw_affiliation_string":"Institute of Computing, Modeling and Their Applications, Clermont-Auvergne University, 63000 Clermont-Ferrand, France","institution_ids":["https://openalex.org/I198244214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350631","display_name":"Le Zhang","orcid":"https://orcid.org/0000-0002-6930-8674"},"institutions":[{"id":"https://openalex.org/I4210156332","display_name":"Chinese Research Academy of Environmental Sciences","ror":"https://ror.org/05t8xvx87","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210156332"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Zhang","raw_affiliation_strings":["Chinese Research Academy of Environmental Sciences, No. 8, Da Yang Fang, An Wai, Chao Yang District, Beijing 100012, China"],"affiliations":[{"raw_affiliation_string":"Chinese Research Academy of Environmental Sciences, No. 8, Da Yang Fang, An Wai, Chao Yang District, Beijing 100012, China","institution_ids":["https://openalex.org/I4210156332"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100663887","display_name":"Xiuhong Li","orcid":"https://orcid.org/0000-0002-8173-2240"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiuhong Li","raw_affiliation_strings":["College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China"],"affiliations":[{"raw_affiliation_string":"College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100663887"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":18.6092,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.99487151,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"15","issue":"3","first_page":"827","last_page":"827"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.995199978351593,"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":0.995199978351593,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.986299991607666,"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"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/computer-science","display_name":"Computer science","score":0.7977073192596436},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7354410886764526},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6374311447143555},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.588911771774292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5833503007888794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4235313832759857},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.41661468148231506},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35334956645965576},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33894801139831543},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2980083227157593}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7977073192596436},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7354410886764526},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6374311447143555},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.588911771774292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5833503007888794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4235313832759857},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.41661468148231506},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35334956645965576},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33894801139831543},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2980083227157593},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15030827","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030827","pdf_url":"https://www.mdpi.com/2072-4292/15/3/827/pdf?version=1675916543","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:42ad096fba524f97a02555c41052a6fa","is_oa":true,"landing_page_url":"https://doaj.org/article/42ad096fba524f97a02555c41052a6fa","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 3, p 827 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/3/827/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15030827","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15030827","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030827","pdf_url":"https://www.mdpi.com/2072-4292/15/3/827/pdf?version=1675916543","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4319019665.pdf"},"referenced_works_count":99,"referenced_works":["https://openalex.org/W751258031","https://openalex.org/W1496056137","https://openalex.org/W1575434449","https://openalex.org/W1691728462","https://openalex.org/W1866230956","https://openalex.org/W1906598733","https://openalex.org/W1970665788","https://openalex.org/W2015619014","https://openalex.org/W2026799324","https://openalex.org/W2070048073","https://openalex.org/W2086642909","https://openalex.org/W2095705004","https://openalex.org/W2108501770","https://openalex.org/W2115403315","https://openalex.org/W2132791018","https://openalex.org/W2135181320","https://openalex.org/W2148143831","https://openalex.org/W2149298154","https://openalex.org/W2165698076","https://openalex.org/W2168876499","https://openalex.org/W2292481059","https://openalex.org/W2343938449","https://openalex.org/W2355274281","https://openalex.org/W2362688718","https://openalex.org/W2376414103","https://openalex.org/W2377980061","https://openalex.org/W2470142083","https://openalex.org/W2594961016","https://openalex.org/W2604262106","https://openalex.org/W2604763608","https://openalex.org/W2614504311","https://openalex.org/W2617669016","https://openalex.org/W2730249686","https://openalex.org/W2743627947","https://openalex.org/W2752796333","https://openalex.org/W2756182389","https://openalex.org/W2766123424","https://openalex.org/W2768359788","https://openalex.org/W2803946476","https://openalex.org/W2809598685","https://openalex.org/W2890833618","https://openalex.org/W2892123021","https://openalex.org/W2900595477","https://openalex.org/W2901130652","https://openalex.org/W2901147009","https://openalex.org/W2941703563","https://openalex.org/W2949736877","https://openalex.org/W2952034878","https://openalex.org/W2954996726","https://openalex.org/W2963031676","https://openalex.org/W2963070905","https://openalex.org/W2963459241","https://openalex.org/W2963470893","https://openalex.org/W2963622428","https://openalex.org/W2963799213","https://openalex.org/W2964127395","https://openalex.org/W2971074500","https://openalex.org/W2971574275","https://openalex.org/W2981798583","https://openalex.org/W2983427092","https://openalex.org/W2992308087","https://openalex.org/W2992511782","https://openalex.org/W3012429074","https://openalex.org/W3014672015","https://openalex.org/W3021017213","https://openalex.org/W3035682985","https://openalex.org/W3035955179","https://openalex.org/W3036479037","https://openalex.org/W3037863642","https://openalex.org/W3046387678","https://openalex.org/W3048924727","https://openalex.org/W3094553346","https://openalex.org/W3110456248","https://openalex.org/W3131868721","https://openalex.org/W3131937156","https://openalex.org/W3171873561","https://openalex.org/W3181770284","https://openalex.org/W3186981108","https://openalex.org/W3196522548","https://openalex.org/W4214587440","https://openalex.org/W4243367342","https://openalex.org/W4248710273","https://openalex.org/W4289761690","https://openalex.org/W4293777495","https://openalex.org/W4307823382","https://openalex.org/W4313156423","https://openalex.org/W4403280031","https://openalex.org/W6637412569","https://openalex.org/W6639118987","https://openalex.org/W6674330103","https://openalex.org/W6675944832","https://openalex.org/W6682208247","https://openalex.org/W6684193495","https://openalex.org/W6696636527","https://openalex.org/W6704734575","https://openalex.org/W6748391871","https://openalex.org/W6752910514","https://openalex.org/W6762931180","https://openalex.org/W6784057640"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W3099765033","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919","https://openalex.org/W4380075502"],"abstract_inverted_index":{"In":[0,45],"recent":[1],"years,":[2],"remote":[3,21,49,133],"sensing":[4,22,50,134],"target":[5,37,52],"recognition":[6,38,53],"algorithms":[7],"based":[8,54,145],"on":[9,55,146],"deep":[10,43,56,102],"learning":[11],"technology":[12],"have":[13,29,93,107],"gradually":[14],"become":[15],"mainstream":[16],"in":[17,32],"the":[18,25,33,40,46,78,84,99,122,126,139,147,154,182,194,197],"field":[19],"of":[20,24,35,42,48,61,73,80,83,101,125,141,150,187,196],"because":[23],"great":[26],"improvements":[27],"that":[28],"been":[30,95,108],"made":[31],"accuracy":[34],"image":[36,51],"through":[39],"use":[41],"learning.":[44],"research":[47,62,74,127,204],"learning,":[57,103],"an":[58,66,81],"insufficient":[59],"number":[60,72],"samples":[63,75],"is":[64,114,138],"often":[65],"encountered":[67],"issue;":[68],"too":[69],"small":[70],"a":[71],"will":[76],"cause":[77],"phenomenon":[79],"overfitting":[82],"model.":[85],"To":[86],"solve":[87],"this":[88,142,172,191],"problem,":[89],"data":[90,130,151,163,168,207],"augmentation":[91,131,152,164,169,208],"techniques":[92],"also":[94],"developed":[96],"along":[97],"with":[98],"popularity":[100],"and":[104,120,166,175,185,200],"many":[105],"methods":[106,156,165,199],"proposed.":[109],"However,":[110],"to":[111,129,180],"date,":[112],"there":[113],"no":[115],"literature":[116],"aimed":[117],"at":[118],"expounding":[119],"summarizing":[121],"current":[123],"state":[124],"applied":[128],"for":[132,206],"object":[135],"recognition,":[136],"which":[137],"purpose":[140],"article.":[143],"First,":[144],"essential":[148],"principles":[149],"methods,":[153],"existing":[155,198],"are":[157],"divided":[158],"into":[159],"two":[160],"categories:":[161],"data-based":[162],"network-based":[167],"methods.":[170,209],"Second,":[171],"paper":[173,192],"subdivides":[174],"compares":[176],"each":[177,188],"method":[178],"category":[179],"show":[181],"advantages,":[183],"disadvantages,":[184],"characteristics":[186],"method.":[189],"Finally,":[190],"discusses":[193],"limitations":[195],"points":[201],"out":[202],"future":[203],"directions":[205]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":50},{"year":2024,"cited_by_count":41},{"year":2023,"cited_by_count":14}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
