{"id":"https://openalex.org/W4324092326","doi":"https://doi.org/10.3390/rs15061552","title":"An Effective Task Sampling Strategy Based on Category Generation for Fine-Grained Few-Shot Object Recognition","display_name":"An Effective Task Sampling Strategy Based on Category Generation for Fine-Grained Few-Shot Object Recognition","publication_year":2023,"publication_date":"2023-03-12","ids":{"openalex":"https://openalex.org/W4324092326","doi":"https://doi.org/10.3390/rs15061552"},"language":"en","primary_location":{"id":"doi:10.3390/rs15061552","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15061552","pdf_url":"https://www.mdpi.com/2072-4292/15/6/1552/pdf?version=1678612142","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":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/6/1552/pdf?version=1678612142","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008113307","display_name":"Shifan Liu","orcid":"https://orcid.org/0000-0003-0432-5358"},"institutions":[{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shifan Liu","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030713988","display_name":"Ailong Ma","orcid":"https://orcid.org/0000-0003-3692-6473"},"institutions":[{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ailong Ma","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049671371","display_name":"Shaoming Pan","orcid":"https://orcid.org/0000-0001-6789-3876"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoming Pan","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100754351","display_name":"Yanfei Zhong","orcid":"https://orcid.org/0000-0001-9446-5850"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfei Zhong","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5030713988"],"corresponding_institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.0509,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8029417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"15","issue":"6","first_page":"1552","last_page":"1552"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"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":0.9959999918937683,"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":0.8493866324424744},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7414190173149109},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6215628385543823},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6200358271598816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6025892496109009},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5584605932235718},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5099741220474243},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42551711201667786},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37980714440345764},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36632072925567627}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8493866324424744},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7414190173149109},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6215628385543823},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6200358271598816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6025892496109009},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5584605932235718},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5099741220474243},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42551711201667786},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37980714440345764},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36632072925567627},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15061552","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15061552","pdf_url":"https://www.mdpi.com/2072-4292/15/6/1552/pdf?version=1678612142","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:11d0456dbe44419699ae9a5029116f77","is_oa":true,"landing_page_url":"https://doaj.org/article/11d0456dbe44419699ae9a5029116f77","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 6, p 1552 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/6/1552/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15061552","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; Volume 15; Issue 6; Pages: 1552","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15061552","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15061552","pdf_url":"https://www.mdpi.com/2072-4292/15/6/1552/pdf?version=1678612142","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":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4324092326.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W56385144","https://openalex.org/W99615980","https://openalex.org/W1905692714","https://openalex.org/W2196230072","https://openalex.org/W2207849498","https://openalex.org/W2256837533","https://openalex.org/W2412588858","https://openalex.org/W2554320282","https://openalex.org/W2591766052","https://openalex.org/W2604763608","https://openalex.org/W2794363191","https://openalex.org/W2807931652","https://openalex.org/W2883502031","https://openalex.org/W2890874825","https://openalex.org/W2911814348","https://openalex.org/W2949346989","https://openalex.org/W2986503696","https://openalex.org/W2987156020","https://openalex.org/W3003180752","https://openalex.org/W3019717150","https://openalex.org/W3101126838","https://openalex.org/W3122279293","https://openalex.org/W3131740536","https://openalex.org/W3161218832","https://openalex.org/W4206470192","https://openalex.org/W4210588976","https://openalex.org/W4214939412","https://openalex.org/W4226456028","https://openalex.org/W4285106710","https://openalex.org/W4296101272","https://openalex.org/W4313063910","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6750222692","https://openalex.org/W6791050018","https://openalex.org/W6839160212","https://openalex.org/W6848347495"],"related_works":["https://openalex.org/W4214877189","https://openalex.org/W2074502265","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W2732813147","https://openalex.org/W2143460112","https://openalex.org/W2042102171"],"abstract_inverted_index":{"The":[0,76,143],"recognition":[1,155],"of":[2,39,50,132,178],"fine-grained":[3,52,103,113,133,169],"objects":[4],"is":[5,15,86],"crucial":[6],"for":[7,68,115],"future":[8],"remote":[9,40,180],"sensing":[10,41,181],"applications,":[11],"but":[12],"this":[13,59,160],"task":[14,65,99,137],"faced":[16],"with":[17],"the":[18,28,36,44,48,73,97,108,116,129,140,148,152,163,176],"few-shot":[19,30,69,170],"problem":[20],"due":[21],"to":[22,55,138,165,168,175],"limited":[23],"labeled":[24],"data.":[25],"In":[26,58],"addition,":[27],"existing":[29,153],"learning":[31,70],"methods":[32],"do":[33],"not":[34],"consider":[35],"unique":[37],"characteristics":[38],"objects,":[42],"i.e.,":[43],"complex":[45],"backgrounds":[46],"and":[47,91,95],"difficulty":[49],"extracting":[51,112],"features,":[53],"leading":[54],"suboptimal":[56],"performance.":[57],"study,":[60],"we":[61],"developed":[62],"an":[63],"improved":[64],"sampling":[66],"strategy":[67,150,161],"that":[71,107,127,147,159],"optimizes":[72],"target":[74,98],"distribution.":[75,104],"proposed":[77,149],"approach":[78],"incorporates":[79],"broad":[80,90,118],"category":[81,93,124],"information,":[82],"where":[83],"each":[84,136],"sample":[85],"assigned":[87],"both":[88],"a":[89,102,123],"fine":[92],"label":[94],"converts":[96],"distribution":[100],"into":[101],"This":[105],"ensures":[106,128],"model":[109,141],"focuses":[110],"on":[111],"features":[114],"corresponding":[117],"category.":[119],"We":[120,157],"also":[121],"introduce":[122],"generation":[125],"method":[126],"same":[130],"number":[131],"categories":[134],"in":[135],"improve":[139],"accuracy.":[142],"experimental":[144],"results":[145],"demonstrate":[146],"outperforms":[151],"object":[154,171],"methods.":[156],"believe":[158],"has":[162],"potential":[164],"be":[166],"applied":[167],"recognition,":[172],"thus":[173],"contributing":[174],"development":[177],"high-precision":[179],"applications.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-01-20T17:24:06.736184","created_date":"2025-10-10T00:00:00"}