{"id":"https://openalex.org/W2783748519","doi":"https://doi.org/10.1109/tip.2019.2917862","title":"Learning Deep Features for One-Class Classification","display_name":"Learning Deep Features for One-Class Classification","publication_year":2019,"publication_date":"2019-05-24","ids":{"openalex":"https://openalex.org/W2783748519","doi":"https://doi.org/10.1109/tip.2019.2917862","mag":"2783748519","pmid":"https://pubmed.ncbi.nlm.nih.gov/31144635"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2917862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2917862","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1801.05365","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Pramuditha Perera","orcid":"https://orcid.org/0000-0003-2821-6367"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pramuditha Perera","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":null,"display_name":"Vishal M. Patel","orcid":"https://orcid.org/0000-0002-5239-692X"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishal M. Patel","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":22.977,"has_fulltext":false,"cited_by_count":285,"citation_normalized_percentile":{"value":0.99563975,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"28","issue":"11","first_page":"5450","last_page":"5463"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9257000088691711,"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":0.9257000088691711,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.017899999395012856,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.010499999858438969,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5997999906539917},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.580299973487854},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5561000108718872},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5404000282287598},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5198000073432922},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5049999952316284},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.487199991941452},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41499999165534973}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7785999774932861},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7391999959945679},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5997999906539917},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.580299973487854},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5561000108718872},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5404000282287598},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5198000073432922},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5049999952316284},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.358599990606308},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3504999876022339},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C18648836","wikidata":"https://www.wikidata.org/wiki/Q381892","display_name":"Compact space","level":2,"score":0.2614000141620636}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2019.2917862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2917862","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:31144635","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31144635","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":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:1801.05365","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.05365","pdf_url":"https://arxiv.org/pdf/1801.05365","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1801.05365","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.05365","pdf_url":"https://arxiv.org/pdf/1801.05365","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G679209862","display_name":null,"funder_award_id":"YIP N00014-16-1-3134","funder_id":"https://openalex.org/F4320338298","funder_display_name":"Office of Naval Research Global"}],"funders":[{"id":"https://openalex.org/F4320338298","display_name":"Office of Naval Research Global","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W571200655","https://openalex.org/W1499399937","https://openalex.org/W1584270973","https://openalex.org/W1970088130","https://openalex.org/W1971751574","https://openalex.org/W2019524107","https://openalex.org/W2025768430","https://openalex.org/W2031489346","https://openalex.org/W2065255264","https://openalex.org/W2081458210","https://openalex.org/W2081604642","https://openalex.org/W2095345875","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2116607081","https://openalex.org/W2121647436","https://openalex.org/W2122646361","https://openalex.org/W2132870739","https://openalex.org/W2138621090","https://openalex.org/W2155893237","https://openalex.org/W2157364932","https://openalex.org/W2194775991","https://openalex.org/W2236636307","https://openalex.org/W2471556897","https://openalex.org/W2533598788","https://openalex.org/W2539476124","https://openalex.org/W2554269471","https://openalex.org/W2732026016","https://openalex.org/W2780495118","https://openalex.org/W2897710659","https://openalex.org/W2905867642","https://openalex.org/W2920322257","https://openalex.org/W2940887512","https://openalex.org/W2963152987","https://openalex.org/W6637373629","https://openalex.org/W6640963894","https://openalex.org/W6681096077","https://openalex.org/W6682778277","https://openalex.org/W6684191040","https://openalex.org/W6713447996","https://openalex.org/W6728797393","https://openalex.org/W6748366383","https://openalex.org/W6751494907","https://openalex.org/W6760425358","https://openalex.org/W6760835899","https://openalex.org/W6760946269"],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,33,46,73],"novel":[3],"deep-learning-based":[4],"approach":[5],"for":[6,20,54],"one-class":[7,24,107],"transfer":[8],"learning":[9,22],"in":[10,23,50],"which":[11],"labeled":[12],"data":[13],"from":[14],"an":[15],"unrelated":[16],"task":[17],"is":[18,81],"used":[19],"feature":[21,52],"classification.":[25],"The":[26],"proposed":[27,70,105],"method":[28,110],"operates":[29],"on":[30,90],"top":[31],"of":[32,38],"convolutional":[34],"neural":[35],"network":[36],"(CNN)":[37],"choice":[39],"and":[40,66,97],"produces":[41],"descriptive":[42],"features":[43],"while":[44],"maintaining":[45],"low":[47],"intra-class":[48],"variance":[49],"the":[51,55,85,104,115],"space":[53],"given":[56],"class.":[57],"For":[58],"this":[59],"purpose":[60],"two":[61],"loss":[62,65],"functions,":[63],"compactness":[64],"descriptiveness":[67],"loss,":[68],"are":[69],"along":[71],"with":[72],"parallel":[74],"CNN":[75],"architecture.":[76],"A":[77],"template":[78],"matching-based":[79],"framework":[80],"introduced":[82],"to":[83],"facilitate":[84],"testing":[86],"process.":[87],"Extensive":[88],"experiments":[89],"publicly":[91],"available":[92],"anomaly":[93],"detection,":[94,96],"novelty":[95],"mobile":[98],"active":[99],"authentication":[100],"datasets":[101],"show":[102],"that":[103],"deep":[106],"(DOC)":[108],"classification":[109],"achieves":[111],"significant":[112],"improvements":[113],"over":[114],"state-of-the-art.":[116]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":57},{"year":2022,"cited_by_count":52},{"year":2021,"cited_by_count":66},{"year":2020,"cited_by_count":37},{"year":2019,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2018-01-26T00:00:00"}
