{"id":"https://openalex.org/W2036707103","doi":"https://doi.org/10.5244/c.26.50","title":"Divergence-Based One-Class Classification Using Gaussian Processes","display_name":"Divergence-Based One-Class Classification Using Gaussian Processes","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W2036707103","doi":"https://doi.org/10.5244/c.26.50","mag":"2036707103"},"language":"en","primary_location":{"id":"doi:10.5244/c.26.50","is_oa":false,"landing_page_url":"https://doi.org/10.5244/c.26.50","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedings of the British Machine Vision Conference 2012","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/A5087931836","display_name":"Paul Bodesheim","orcid":"https://orcid.org/0000-0002-3564-6528"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Paul Bodesheim","raw_affiliation_strings":["University of Jena"],"affiliations":[{"raw_affiliation_string":"University of Jena","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018098456","display_name":"Erik Rodner","orcid":"https://orcid.org/0000-0002-3711-1498"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erik Rodner","raw_affiliation_strings":["University of Jena"],"affiliations":[{"raw_affiliation_string":"University of Jena","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073470730","display_name":"Alexander Freytag","orcid":"https://orcid.org/0000-0002-9041-1334"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexander Freytag","raw_affiliation_strings":["University of Jena"],"affiliations":[{"raw_affiliation_string":"University of Jena","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024934744","display_name":"Joachim Denzler","orcid":"https://orcid.org/0000-0002-3193-3300"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joachim Denzler","raw_affiliation_strings":["University of Jena"],"affiliations":[{"raw_affiliation_string":"University of Jena","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087931836"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7685,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.86573554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"50.1","last_page":"50.11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9993000030517578,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9993000030517578,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9970999956130981,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.993399977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.7648993730545044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6930906772613525},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6749955415725708},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6436740756034851},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.636044979095459},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5880096554756165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5747940540313721},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.5640630722045898},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.560462474822998},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.533128023147583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4756057858467102},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.468778520822525},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.460148423910141},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4336596131324768},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32635802030563354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28886640071868896}],"concepts":[{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.7648993730545044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6930906772613525},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6749955415725708},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6436740756034851},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.636044979095459},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5880096554756165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5747940540313721},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.5640630722045898},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.560462474822998},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.533128023147583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4756057858467102},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.468778520822525},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.460148423910141},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4336596131324768},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32635802030563354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28886640071868896},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5244/c.26.50","is_oa":false,"landing_page_url":"https://doi.org/10.5244/c.26.50","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedings of the British Machine Vision Conference 2012","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.673.978","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.673.978","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.inf-cv.uni-jena.de/dbvmedia/de/Research/Novelty_Detection/Bodesheim12_DOC.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1488833649","https://openalex.org/W1506806321","https://openalex.org/W1574277932","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1764474518","https://openalex.org/W1970088130","https://openalex.org/W2007864935","https://openalex.org/W2027248184","https://openalex.org/W2108598243","https://openalex.org/W2109646585","https://openalex.org/W2136111243","https://openalex.org/W2146950091","https://openalex.org/W2157826563","https://openalex.org/W2334018742","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W2064636555","https://openalex.org/W2585503716","https://openalex.org/W1939982668","https://openalex.org/W2105014086","https://openalex.org/W2076090200","https://openalex.org/W3025682415","https://openalex.org/W2081173909","https://openalex.org/W4389009659","https://openalex.org/W4312933423","https://openalex.org/W2604316291"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2],"information":[3],"theoretic":[4],"framework":[5],"for":[6,11],"one-class":[7],"classification,":[8],"which":[9],"allows":[10],"deriving":[12],"several":[13],"new":[14],"novelty":[15,29],"scores.":[16],"With":[17],"these":[18],"scores,":[19],"we":[20],"are":[21],"able":[22],"to":[23,27,31,36,48,101],"rank":[24],"samples":[25],"according":[26],"their":[28],"and":[30,72],"detect":[32],"outliers":[33],"not":[34],"belonging":[35],"a":[37,53,66],"learnt":[38,59],"data":[39],"distribution.":[40],"The":[41],"key":[42],"idea":[43],"of":[44,52],"our":[45],"approach":[46],"is":[47,62,84],"measure":[49],"the":[50,57,77],"impact":[51],"test":[54],"sample":[55],"on":[56],"previously":[58],"model.":[60],"This":[61],"carried":[63],"out":[64],"in":[65],"probabilistic":[67],"manner":[68],"using":[69,86],"Jensen-Shannon":[70],"divergence":[71],"reclassification":[73],"results":[74],"derived":[75],"from":[76],"Gaussian":[78],"pro-cess":[79],"regression":[80],"framework.":[81],"Our":[82],"method":[83],"evaluated":[85],"well-known":[87],"machine":[88],"learning":[89],"datasets":[90],"as":[91,93],"well":[92],"large-scale":[94],"image":[95],"categorisation":[96],"experiments":[97],"showing":[98],"its":[99],"ability":[100],"achieve":[102],"state-of-the-art":[103],"performance.":[104],"1":[105]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
