{"id":"https://openalex.org/W2948947774","doi":"https://doi.org/10.1186/s41074-019-0056-0","title":"Unsupervised anomaly detection with compact deep features for wind turbine blade images taken by a drone","display_name":"Unsupervised anomaly detection with compact deep features for wind turbine blade images taken by a drone","publication_year":2019,"publication_date":"2019-06-04","ids":{"openalex":"https://openalex.org/W2948947774","doi":"https://doi.org/10.1186/s41074-019-0056-0","mag":"2948947774"},"language":"en","primary_location":{"id":"doi:10.1186/s41074-019-0056-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s41074-019-0056-0","pdf_url":"https://ipsjcva.springeropen.com/track/pdf/10.1186/s41074-019-0056-0","source":{"id":"https://openalex.org/S10995576","display_name":"IPSJ Transactions on Computer Vision and Applications","issn_l":"1882-6695","issn":["1882-6695"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IPSJ Transactions on Computer Vision and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ipsjcva.springeropen.com/track/pdf/10.1186/s41074-019-0056-0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100429059","display_name":"Yi-Nan Wang","orcid":"https://orcid.org/0000-0001-7418-1519"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yinan Wang","raw_affiliation_strings":["The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026866776","display_name":"Ryota Yoshihashi","orcid":"https://orcid.org/0000-0002-1194-9663"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryota Yoshihashi","raw_affiliation_strings":["The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113695192","display_name":"Rei Kawakami","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rei Kawakami","raw_affiliation_strings":["The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003277535","display_name":"Shaodi You","orcid":"https://orcid.org/0000-0001-8973-645X"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"funder","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shaodi You","raw_affiliation_strings":["Data61-CSIRO, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Data61-CSIRO, Canberra, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076815468","display_name":"Tohru Harano","orcid":null},"institutions":[{"id":"https://openalex.org/I164917862","display_name":"J-Power (Japan)","ror":"https://ror.org/04rbbpv92","country_code":"JP","type":"company","lineage":["https://openalex.org/I164917862"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tohru Harano","raw_affiliation_strings":["Eco Power Co., Ltd., TOC Osaki Bldg.1, 1-6-1 Osaki, Shinagawa-ku, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Eco Power Co., Ltd., TOC Osaki Bldg.1, 1-6-1 Osaki, Shinagawa-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I164917862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008702485","display_name":"Masahiko Ito","orcid":null},"institutions":[{"id":"https://openalex.org/I164917862","display_name":"J-Power (Japan)","ror":"https://ror.org/04rbbpv92","country_code":"JP","type":"company","lineage":["https://openalex.org/I164917862"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiko Ito","raw_affiliation_strings":["Eco Power Co., Ltd., TOC Osaki Bldg.1, 1-6-1 Osaki, Shinagawa-ku, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Eco Power Co., Ltd., TOC Osaki Bldg.1, 1-6-1 Osaki, Shinagawa-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I164917862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082559369","display_name":"Katsura Komagome","orcid":null},"institutions":[{"id":"https://openalex.org/I164917862","display_name":"J-Power (Japan)","ror":"https://ror.org/04rbbpv92","country_code":"JP","type":"company","lineage":["https://openalex.org/I164917862"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Katsura Komagome","raw_affiliation_strings":["Eco Power Co., Ltd., TOC Osaki Bldg.1, 1-6-1 Osaki, Shinagawa-ku, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Eco Power Co., Ltd., TOC Osaki Bldg.1, 1-6-1 Osaki, Shinagawa-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I164917862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101438728","display_name":"Makoto Iida","orcid":"https://orcid.org/0000-0003-0706-5758"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Makoto Iida","raw_affiliation_strings":["The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067212480","display_name":"Takeshi Naemura","orcid":"https://orcid.org/0000-0002-6653-000X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeshi Naemura","raw_affiliation_strings":["The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, 7 Chome-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5100429059"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":3.3238,"has_fulltext":true,"cited_by_count":48,"citation_normalized_percentile":{"value":0.93880507,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9907000064849854,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9907000064849854,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T12086","display_name":"Structural Integrity and Reliability Analysis","score":0.9635999798774719,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/drone","display_name":"Drone","score":0.9271247386932373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7858061194419861},{"id":"https://openalex.org/keywords/blade","display_name":"Blade (archaeology)","score":0.7286806106567383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7049071788787842},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5911312103271484},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5641226172447205},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5386481285095215},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5349553823471069},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5051448941230774},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49528375267982483},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4918403625488281},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4382721185684204},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1408747434616089}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.9271247386932373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7858061194419861},{"id":"https://openalex.org/C2776132848","wikidata":"https://www.wikidata.org/wiki/Q3045036","display_name":"Blade (archaeology)","level":2,"score":0.7286806106567383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049071788787842},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5911312103271484},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5641226172447205},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5386481285095215},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5349553823471069},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5051448941230774},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49528375267982483},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4918403625488281},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4382721185684204},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1408747434616089},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s41074-019-0056-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s41074-019-0056-0","pdf_url":"https://ipsjcva.springeropen.com/track/pdf/10.1186/s41074-019-0056-0","source":{"id":"https://openalex.org/S10995576","display_name":"IPSJ Transactions on Computer Vision and Applications","issn_l":"1882-6695","issn":["1882-6695"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IPSJ Transactions on Computer Vision and Applications","raw_type":"journal-article"},{"id":"pmh:oai:dare.uva.nl:openaire_cris_publications/de475b71-0227-4a30-adda-d85eb19752d1","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/unsupervised-anomaly-detection-with-compact-deep-features-for-wind-turbine-blade-images-taken-by-a-drone(de475b71-0227-4a30-adda-d85eb19752d1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wang, Y, Yoshihashi, R, Kawakami, R, You, S, Harano, T, Ito, M, Komagome, K, Iida, M & Naemura, T 2019, 'Unsupervised anomaly detection with compact deep features for wind turbine blade images taken by a drone', IPSJ Transactions on Computer Vision and Applications, vol. 11, no. 1, 3. https://doi.org/10.1186/s41074-019-0056-0","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:dare.uva.nl:publications/de475b71-0227-4a30-adda-d85eb19752d1","is_oa":true,"landing_page_url":"https://hdl.handle.net/11245.1/de475b71-0227-4a30-adda-d85eb19752d1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"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":"Wang, Y, Yoshihashi, R, Kawakami, R, You, S, Harano, T, Ito, M, Komagome, K, Iida, M & Naemura, T 2019, 'Unsupervised anomaly detection with compact deep features for wind turbine blade images taken by a drone', IPSJ Transactions on Computer Vision and Applications, vol. 11, no. 1, 3. https://doi.org/10.1186/s41074-019-0056-0","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:99c06eb14f814a7590e09e610fbd7063","is_oa":true,"landing_page_url":"https://doaj.org/article/99c06eb14f814a7590e09e610fbd7063","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IPSJ Transactions on Computer Vision and Applications, Vol 11, Iss 1, Pp 1-7 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s41074-019-0056-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s41074-019-0056-0","pdf_url":"https://ipsjcva.springeropen.com/track/pdf/10.1186/s41074-019-0056-0","source":{"id":"https://openalex.org/S10995576","display_name":"IPSJ Transactions on Computer Vision and Applications","issn_l":"1882-6695","issn":["1882-6695"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IPSJ Transactions on Computer Vision and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8899999856948853}],"awards":[{"id":"https://openalex.org/G2614383054","display_name":null,"funder_award_id":"JP18K1","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3236194794","display_name":null,"funder_award_id":"Grant-in-Aid","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3374257489","display_name":null,"funder_award_id":"JP16J04552","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3459562248","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4227499671","display_name":null,"funder_award_id":"KAKENHI Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4403406518","display_name":"\u91ce\u9ce5\u306e\u5e83\u57df\u76e3\u8996\u306b\u5411\u3051\u305f\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u753b\u50cf\u8a8d\u8b58\u306e\u7814\u7a76","funder_award_id":"16J04552","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4874944895","display_name":null,"funder_award_id":"-in-Aid","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G497396822","display_name":"Development of deep neural network architecture for multitask learning","funder_award_id":"18K11348","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5786340949","display_name":null,"funder_award_id":"KAKENHI Grant Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7641758827","display_name":null,"funder_award_id":"JP18K11348","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7752643416","display_name":null,"funder_award_id":"Japan","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8430481527","display_name":null,"funder_award_id":"Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2948947774.pdf","grobid_xml":"https://content.openalex.org/works/W2948947774.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1676763678","https://openalex.org/W1686810756","https://openalex.org/W1994533780","https://openalex.org/W2062118960","https://openalex.org/W2121598944","https://openalex.org/W2132870739","https://openalex.org/W2136655611","https://openalex.org/W2161969291","https://openalex.org/W2340896621","https://openalex.org/W2598457882","https://openalex.org/W2599354622","https://openalex.org/W2786088545","https://openalex.org/W2963149653"],"related_works":["https://openalex.org/W4229448053","https://openalex.org/W4247925126","https://openalex.org/W4327774218","https://openalex.org/W2059768187","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W4379143281","https://openalex.org/W2605096541","https://openalex.org/W3200286695","https://openalex.org/W4212885606"],"abstract_inverted_index":{"Abstract":[0],"Detecting":[1],"anomalies":[2,115],"in":[3,104,116],"wind":[4],"turbine":[5],"blades":[6],"from":[7,70],"aerial":[8],"images":[9,76],"taken":[10,77],"by":[11,56,78,90],"drones":[12],"can":[13],"reduce":[14],"the":[15,85,105],"costs":[16],"of":[17,32,53,108],"periodic":[18],"inspections.":[19],"Deep":[20],"learning":[21,64],"is":[22],"useful":[23,112],"for":[24,113],"image":[25,73],"recognition,":[26],"but":[27],"it":[28],"requires":[29],"large":[30],"amounts":[31],"data":[33],"to":[34,47,84,96],"be":[35],"collected":[36],"on":[37],"rare":[38],"abnormalities.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"propose":[44],"a":[45,54,71,79],"method":[46],"distinguish":[48],"normal":[49],"and":[50,88],"abnormal":[51],"parts":[52],"blade":[55,117],"combining":[57],"one-class":[58],"support":[59],"vector":[60],"machine,":[61],"an":[62],"unsupervised":[63],"method,":[65],"with":[66],"deep":[67,109],"features":[68,103],"learned":[69],"generic":[72],"dataset.":[74],"The":[75],"drone":[80],"are":[81,111],"subsampled,":[82],"projected":[83],"feature":[86],"space,":[87],"compressed":[89],"using":[91],"principle":[92],"component":[93],"analysis":[94],"(PCA)":[95],"make":[97],"them":[98],"learnable.":[99],"Experiments":[100],"show":[101],"that":[102],"lower":[106],"layers":[107],"nets":[110],"detecting":[114],"images.":[118]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}