{"id":"https://openalex.org/W4210763918","doi":"https://doi.org/10.1109/globecom46510.2021.9685826","title":"ATTL: An Automated Targeted Transfer Learning with Deep Neural Networks","display_name":"ATTL: An Automated Targeted Transfer Learning with Deep Neural Networks","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4210763918","doi":"https://doi.org/10.1109/globecom46510.2021.9685826"},"language":"en","primary_location":{"id":"doi:10.1109/globecom46510.2021.9685826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom46510.2021.9685826","pdf_url":null,"source":{"id":"https://openalex.org/S4363607714","display_name":"2021 IEEE Global Communications Conference (GLOBECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-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/A5001461808","display_name":"Sayyed Farid Ahamed","orcid":null},"institutions":[{"id":"https://openalex.org/I4210138378","display_name":"Dominion (United States)","ror":"https://ror.org/038q98v71","country_code":"US","type":"company","lineage":["https://openalex.org/I4210138378"]},{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sayyed Farid Ahamed","raw_affiliation_strings":["Virginia Modeling, Analysis and Simulation Center, Old Dominion University,Virginia,USA","Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Modeling, Analysis and Simulation Center, Old Dominion University,Virginia,USA","institution_ids":["https://openalex.org/I81365321","https://openalex.org/I4210138378"]},{"raw_affiliation_string":"Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Virginia, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019081200","display_name":"Priyanka Aggarwal","orcid":"https://orcid.org/0000-0002-6760-2191"},"institutions":[{"id":"https://openalex.org/I4210138378","display_name":"Dominion (United States)","ror":"https://ror.org/038q98v71","country_code":"US","type":"company","lineage":["https://openalex.org/I4210138378"]},{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Priyanka Aggarwal","raw_affiliation_strings":["Virginia Modeling, Analysis and Simulation Center, Old Dominion University,Virginia,USA","Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Modeling, Analysis and Simulation Center, Old Dominion University,Virginia,USA","institution_ids":["https://openalex.org/I81365321","https://openalex.org/I4210138378"]},{"raw_affiliation_string":"Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Virginia, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052787847","display_name":"Sachin Shetty","orcid":"https://orcid.org/0000-0002-8789-0610"},"institutions":[{"id":"https://openalex.org/I4210138378","display_name":"Dominion (United States)","ror":"https://ror.org/038q98v71","country_code":"US","type":"company","lineage":["https://openalex.org/I4210138378"]},{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sachin Shetty","raw_affiliation_strings":["Virginia Modeling, Analysis and Simulation Center, Old Dominion University,Virginia,USA","Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Modeling, Analysis and Simulation Center, Old Dominion University,Virginia,USA","institution_ids":["https://openalex.org/I81365321","https://openalex.org/I4210138378"]},{"raw_affiliation_string":"Virginia Modeling, Analysis and Simulation Center, Old Dominion University, Virginia, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054460502","display_name":"Erin Lanus","orcid":"https://orcid.org/0000-0001-8263-0521"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erin Lanus","raw_affiliation_strings":["Hume Center, Virginia Tech,Virginia,USA","Hume Center, Virginia Tech, Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hume Center, Virginia Tech,Virginia,USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Hume Center, Virginia Tech, Virginia, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059050900","display_name":"Laura Freeman","orcid":"https://orcid.org/0000-0001-7108-3921"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Laura J. Freeman","raw_affiliation_strings":["Virginia Tech,Dept. of Statistics,Virginia,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech,Dept. of Statistics,Virginia,USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.761,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.75757856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9991999864578247,"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":0.9991999864578247,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9907000064849854,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.977400004863739,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.784844160079956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7571349143981934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6429420709609985},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.5347188115119934},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5067594647407532},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5022094249725342},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48188287019729614},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46981385350227356},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3290242552757263}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.784844160079956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7571349143981934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6429420709609985},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.5347188115119934},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5067594647407532},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5022094249725342},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48188287019729614},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46981385350227356},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3290242552757263},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom46510.2021.9685826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom46510.2021.9685826","pdf_url":null,"source":{"id":"https://openalex.org/S4363607714","display_name":"2021 IEEE Global Communications Conference (GLOBECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4099999964237213}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1987220198","https://openalex.org/W2591924527","https://openalex.org/W2617869948","https://openalex.org/W2736761179","https://openalex.org/W2809254203","https://openalex.org/W2901474455","https://openalex.org/W2940934424","https://openalex.org/W2963460174","https://openalex.org/W2973459053","https://openalex.org/W2997265920","https://openalex.org/W3003687182","https://openalex.org/W3009371949","https://openalex.org/W3011613491","https://openalex.org/W3023764908","https://openalex.org/W3170449064","https://openalex.org/W6738103906","https://openalex.org/W6756344106","https://openalex.org/W6773416768","https://openalex.org/W6775159726"],"related_works":["https://openalex.org/W3192840557","https://openalex.org/W4380075502","https://openalex.org/W2889705046","https://openalex.org/W4223943233","https://openalex.org/W4360585206","https://openalex.org/W4312200629","https://openalex.org/W4382286161","https://openalex.org/W4386213806","https://openalex.org/W2960456850","https://openalex.org/W4317565044"],"abstract_inverted_index":{"Success":[0],"of":[1,26,156,168,178],"machine":[2],"learning":[3,28,61,176],"algorithms":[4],"hinges":[5],"on":[6,113,139],"access":[7],"to":[8,23,64,94,107,172],"labeled":[9,13],"dataset.":[10],"Obtaining":[11],"a":[12,36,130,153],"dataset":[14,146],"is":[15,84],"an":[16,57],"expensive,":[17],"challenging":[18],"and":[19,70,118,147],"time-consuming":[20],"process,":[21],"leading":[22],"the":[24,66,96,105,136,140,148,161,173],"development":[25],"transfer":[27,60,175],"(TL)":[29],"methodology.":[30],"TL":[31],"incorporates":[32],"gained":[33],"knowledge":[34],"from":[35,160],"previously":[37],"trained":[38],"source":[39,69,92,125,132],"model":[40,87,166],"into":[41],"specific":[42,124],"yet":[43],"similar":[44],"task":[45],"models":[46],"with":[47,72,90,123],"limited":[48],"data":[49,74,83,111,126],"domain":[50],"coverage.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55],"propose":[56],"automated":[58],"targeted":[59],"(ATTL)":[62],"method":[63,78,138],"resolve":[65],"transferability":[67],"between":[68],"target":[71,82,110,162],"minimal":[73,109],"requirements.":[75],"The":[76,101],"ATTL":[77,102,137],"decides":[79],"how":[80],"much":[81],"essential":[85],"for":[86,127],"training,":[88],"along":[89,122],"selected":[91],"data,":[93],"obtain":[95],"skateholder's":[97],"specified":[98],"performance":[99,167],"metrics.":[100],"framework":[103],"optimizes":[104],"system":[106],"select":[108],"based":[112],"two":[114],"approaches:":[115],"combinatorial":[116],"coverage":[117],"adaptive":[119],"selection":[120],"methodology,":[121],"fine-tuning":[128],"given":[129],"pre-trained":[131],"model.":[133],"We":[134],"evaluated":[135],"Kaggle's":[141],"\u2018planes":[142],"in":[143,170],"satellite":[144],"imagery\u2019":[145],"results":[149],"identified":[150],"that":[151],"acquiring":[152],"small":[154],"number":[155],"intentionally":[157],"well-chosen":[158],"samples":[159],"environment":[163],"can":[164],"achieve":[165],"97%":[169],"comparison":[171],"baseline":[174],"accuracy":[177],"92%.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
