{"id":"https://openalex.org/W4285394646","doi":"https://doi.org/10.3390/s22145244","title":"Non-Deep Active Learning for Deep Neural Networks","display_name":"Non-Deep Active Learning for Deep Neural Networks","publication_year":2022,"publication_date":"2022-07-13","ids":{"openalex":"https://openalex.org/W4285394646","doi":"https://doi.org/10.3390/s22145244","pmid":"https://pubmed.ncbi.nlm.nih.gov/35890924"},"language":"en","primary_location":{"id":"doi:10.3390/s22145244","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22145244","pdf_url":"https://www.mdpi.com/1424-8220/22/14/5244/pdf?version=1657721889","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/14/5244/pdf?version=1657721889","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081632375","display_name":"Yasufumi Kawano","orcid":"https://orcid.org/0000-0002-2252-1910"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasufumi Kawano","raw_affiliation_strings":["Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014083942","display_name":"Yoshiki Nota","orcid":null},"institutions":[{"id":"https://openalex.org/I101979096","display_name":"Meidensha (Japan)","ror":"https://ror.org/047dt4g31","country_code":"JP","type":"company","lineage":["https://openalex.org/I101979096"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiki Nota","raw_affiliation_strings":["Meidensha Corporation, 2-1-1, Osaki, Shinagawa, Tokyo 141-0032, Japan"],"affiliations":[{"raw_affiliation_string":"Meidensha Corporation, 2-1-1, Osaki, Shinagawa, Tokyo 141-0032, Japan","institution_ids":["https://openalex.org/I101979096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040004701","display_name":"Rinpei Mochizuki","orcid":null},"institutions":[{"id":"https://openalex.org/I101979096","display_name":"Meidensha (Japan)","ror":"https://ror.org/047dt4g31","country_code":"JP","type":"company","lineage":["https://openalex.org/I101979096"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rinpei Mochizuki","raw_affiliation_strings":["Meidensha Corporation, 2-1-1, Osaki, Shinagawa, Tokyo 141-0032, Japan"],"affiliations":[{"raw_affiliation_string":"Meidensha Corporation, 2-1-1, Osaki, Shinagawa, Tokyo 141-0032, Japan","institution_ids":["https://openalex.org/I101979096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070908826","display_name":"Yoshimitsu Aoki","orcid":"https://orcid.org/0000-0001-7361-0027"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yoshimitsu Aoki","raw_affiliation_strings":["Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070908826"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.276,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6190903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"22","issue":"14","first_page":"5244","last_page":"5244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9997000098228455,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9815999865531921,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9660999774932861,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8009340763092041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7894997596740723},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6374249458312988},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.596932053565979},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5711294412612915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5496993660926819},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5049596428871155},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.5005192756652832},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.49075374007225037},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44282591342926025},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42760026454925537},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08570995926856995}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8009340763092041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7894997596740723},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6374249458312988},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.596932053565979},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5711294412612915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5496993660926819},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5049596428871155},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.5005192756652832},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.49075374007225037},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44282591342926025},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42760026454925537},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08570995926856995},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22145244","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22145244","pdf_url":"https://www.mdpi.com/1424-8220/22/14/5244/pdf?version=1657721889","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:35890924","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35890924","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:edcaea98a6ce4bbbacad2467668e5506","is_oa":true,"landing_page_url":"https://doaj.org/article/edcaea98a6ce4bbbacad2467668e5506","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":"Sensors, Vol 22, Iss 14, p 5244 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/14/5244/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22145244","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":"Sensors; Volume 22; Issue 14; Pages: 5244","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9319968","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9319968","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22145244","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22145244","pdf_url":"https://www.mdpi.com/1424-8220/22/14/5244/pdf?version=1657721889","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285394646.pdf","grobid_xml":"https://content.openalex.org/works/W4285394646.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W1845402413","https://openalex.org/W1967447455","https://openalex.org/W1983521647","https://openalex.org/W2012127929","https://openalex.org/W2034747098","https://openalex.org/W2101234009","https://openalex.org/W2128678390","https://openalex.org/W2150045166","https://openalex.org/W2188365844","https://openalex.org/W2233838193","https://openalex.org/W2340897893","https://openalex.org/W2460470859","https://openalex.org/W2471138382","https://openalex.org/W2625559849","https://openalex.org/W2798820905","https://openalex.org/W2956371155","https://openalex.org/W2962850830","https://openalex.org/W2964059111","https://openalex.org/W2986514296","https://openalex.org/W3005680577","https://openalex.org/W3035499919","https://openalex.org/W3107725941","https://openalex.org/W3171007011","https://openalex.org/W3175994565","https://openalex.org/W3179550234","https://openalex.org/W3182493068","https://openalex.org/W3209539562","https://openalex.org/W4320013936","https://openalex.org/W6641926478","https://openalex.org/W6675354045","https://openalex.org/W6679227803","https://openalex.org/W6687045409","https://openalex.org/W6696346101","https://openalex.org/W6735374517","https://openalex.org/W6756615331","https://openalex.org/W6797803908"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2556260348"],"abstract_inverted_index":{"One":[0],"way":[1],"to":[2,15,116,171,182],"improve":[3,25],"annotation":[4],"efficiency":[5],"is":[6,14,102,130],"active":[7,12,163],"learning.":[8],"The":[9,78,187],"goal":[10],"of":[11,28,52,145],"learning":[13,31,164],"select":[16,36,139],"images":[17],"from":[18,177],"many":[19],"unlabeled":[20,40,75,93,106],"images,":[21,41,87],"where":[22],"labeling":[23],"will":[24],"the":[26,29,33,37,90,142,146,155,191],"accuracy":[27,160,197],"machine":[30],"model":[32,84,91],"most.":[34],"To":[35],"most":[38],"informative":[39],"conventional":[42,162],"methods":[43,165],"use":[44],"deep":[45],"neural":[46,64],"networks":[47],"with":[48,109],"a":[49,62,82,110,118,133],"large":[50],"number":[51],"computation":[53,57],"nodes":[54],"and":[55,88,122,136,169],"long":[56],"time,":[58],"but":[59],"we":[60],"propose":[61],"non-deep":[63],"network":[65],"method":[66,80,129,157,189,194],"that":[67,154],"does":[68],"not":[69],"require":[70],"any":[71],"additional":[72],"training":[73],"for":[74,104,125],"image":[76],"selection.":[77],"proposed":[79,128,156,188],"trains":[81],"task":[83],"on":[85,96,132,150,166,198],"labeled":[86],"then":[89],"predicts":[92],"images.":[94],"Based":[95],"this":[97],"prediction,":[98],"an":[99],"uncertainty":[100,112],"indicator":[101],"generated":[103],"each":[105],"image.":[107],"Images":[108],"high":[111,119],"index":[113],"are":[114,123],"considered":[115],"have":[117],"information":[120],"content,":[121],"selected":[124],"annotation.":[126],"Our":[127],"based":[131],"very":[134],"simple":[135],"powerful":[137],"idea:":[138],"samples":[140],"near":[141],"decision":[143],"boundary":[144],"model.":[147],"Experimental":[148],"results":[149],"multiple":[151,167],"datasets":[152],"show":[153],"achieves":[158],"higher":[159],"than":[161],"tasks":[168],"up":[170],"14":[172],"times":[173],"faster":[174],"execution":[175],"time":[176],"1.2":[178],"\u00d7":[179,184],"106":[180],"s":[181],"8.3":[183],"104":[185],"s.":[186],"outperforms":[190],"current":[192],"SoTA":[193],"by":[195],"1%":[196],"CIFAR-10.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
