{"id":"https://openalex.org/W4312417111","doi":"https://doi.org/10.1109/tpami.2022.3227913","title":"Orientational Distribution Learning with Hierarchical Spatial Attention for Open Set Recognition","display_name":"Orientational Distribution Learning with Hierarchical Spatial Attention for Open Set Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312417111","doi":"https://doi.org/10.1109/tpami.2022.3227913","pmid":"https://pubmed.ncbi.nlm.nih.gov/37015492"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3227913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3227913","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5038197310","display_name":"Zhunga Liu","orcid":"https://orcid.org/0000-0001-7144-7449"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhun-ga Liu","raw_affiliation_strings":["School of Automation, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-7144-7449","affiliations":[{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069081429","display_name":"Yimin Fu","orcid":"https://orcid.org/0000-0003-2070-995X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi-min Fu","raw_affiliation_strings":["School of Automation, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108517562","display_name":"Quan Pan","orcid":"https://orcid.org/0000-0001-8162-2896"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Pan","raw_affiliation_strings":["School of Automation, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-8162-2896","affiliations":[{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011848136","display_name":"Zuowei Zhang","orcid":"https://orcid.org/0000-0002-4855-5924"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuo-wei Zhang","raw_affiliation_strings":["School of Automation, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-4855-5924","affiliations":[{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":7.6522,"has_fulltext":false,"cited_by_count":70,"citation_normalized_percentile":{"value":0.97792953,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"45","issue":"7","first_page":"1","last_page":"16"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T12676","display_name":"Machine Learning and ELM","score":0.9819999933242798,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9771000146865845,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7203720808029175},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.67913818359375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6779124736785889},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6675522327423096},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.631517767906189},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5759108662605286},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5714601874351501},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5619480609893799},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5328116416931152},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44208014011383057},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4124756157398224}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7203720808029175},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.67913818359375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6779124736785889},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6675522327423096},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.631517767906189},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5759108662605286},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5714601874351501},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5619480609893799},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5328116416931152},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44208014011383057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4124756157398224},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3227913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3227913","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37015492","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37015492","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W572355794","https://openalex.org/W967544008","https://openalex.org/W1032927584","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1846799578","https://openalex.org/W1959608418","https://openalex.org/W2018459374","https://openalex.org/W2096733369","https://openalex.org/W2100332042","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2119880843","https://openalex.org/W2138011018","https://openalex.org/W2157364932","https://openalex.org/W2163605009","https://openalex.org/W2194321275","https://openalex.org/W2194775991","https://openalex.org/W2248269543","https://openalex.org/W2335728318","https://openalex.org/W2466114631","https://openalex.org/W2520774990","https://openalex.org/W2526075485","https://openalex.org/W2531327146","https://openalex.org/W2551176409","https://openalex.org/W2555897561","https://openalex.org/W2577946330","https://openalex.org/W2769159728","https://openalex.org/W2787720882","https://openalex.org/W2895752198","https://openalex.org/W2901114541","https://openalex.org/W2904509905","https://openalex.org/W2922509574","https://openalex.org/W2952140516","https://openalex.org/W2962898354","https://openalex.org/W2963149653","https://openalex.org/W2963314614","https://openalex.org/W2963466847","https://openalex.org/W2963744743","https://openalex.org/W2963875483","https://openalex.org/W2963924212","https://openalex.org/W2969985801","https://openalex.org/W2973218493","https://openalex.org/W2991234496","https://openalex.org/W2991642706","https://openalex.org/W3034748927","https://openalex.org/W3035081753","https://openalex.org/W3035224069","https://openalex.org/W3095099350","https://openalex.org/W3106653142","https://openalex.org/W3118608800","https://openalex.org/W3118707261","https://openalex.org/W3134961575","https://openalex.org/W3157122767","https://openalex.org/W3177034761","https://openalex.org/W3195126467","https://openalex.org/W3202829947","https://openalex.org/W4205598956","https://openalex.org/W4214756262","https://openalex.org/W4226489086","https://openalex.org/W4286905471","https://openalex.org/W6625168331","https://openalex.org/W6637373629","https://openalex.org/W6638677478","https://openalex.org/W6640963894","https://openalex.org/W6684191040","https://openalex.org/W6703116779","https://openalex.org/W6726946684","https://openalex.org/W6728622933","https://openalex.org/W6730323794","https://openalex.org/W6732248266","https://openalex.org/W6745901624","https://openalex.org/W6754995574","https://openalex.org/W6779525423","https://openalex.org/W6787972765","https://openalex.org/W6791774990","https://openalex.org/W6802159084","https://openalex.org/W6811341590"],"related_works":["https://openalex.org/W2905271011","https://openalex.org/W3164948662","https://openalex.org/W4289536128","https://openalex.org/W3153597579","https://openalex.org/W1872833176","https://openalex.org/W4231537015","https://openalex.org/W2020613036","https://openalex.org/W2137791473","https://openalex.org/W2786094008","https://openalex.org/W3131501806"],"abstract_inverted_index":{"Open":[0],"set":[1,104],"recognition":[2,22],"(OSR)":[3],"aims":[4],"to":[5,36,95,114,117,138,164],"correctly":[6],"recognize":[7],"the":[8,13,18,21,38,45,51,62,86,97,119,124,140,154,166,171],"known":[9,42],"classes":[10,15],"and":[11,145,149,170,193],"reject":[12],"unknown":[14],"for":[16,82,102,175],"increasing":[17],"reliability":[19],"of":[20,41,65,89,99,184],"system.":[23],"The":[24,182],"distance-based":[25],"loss":[26],"is":[27,47,92,112,136,162],"often":[28],"employed":[29],"in":[30,55,123],"deep":[31],"neural":[32],"networks-based":[33],"OSR":[34],"methods":[35],"constrain":[37],"latent":[39],"representation":[40,91,155],"classes.":[43],"However,":[44],"optimization":[46],"usually":[48],"conducted":[49],"using":[50],"nondirectional":[52],"euclidean":[53],"distance":[54],"a":[56,107,132,158,177],"single":[57],"feature":[58,90,125,134,168,173],"space":[59,126,135,169,174],"without":[60],"considering":[61],"potential":[63],"impact":[64],"spatial":[66,80,87,109,129],"distribution.":[67],"To":[68],"address":[69],"this":[70],"problem,":[71],"we":[72],"propose":[73],"orientational":[74],"distribution":[75,88,121],"learning":[76],"(ODL)":[77],"with":[78],"hierarchical":[79,108],"attention":[81,110],"OSR.":[83],"In":[84],"ODL,":[85],"optimized":[93],"orientationally":[94],"increase":[96],"discriminability":[98],"decision":[100],"boundaries":[101],"open":[103],"recognition.":[105],"Then,":[106],"mechanism":[111],"proposed":[113],"assist":[115],"ODL":[116,185,194],"capture":[118],"global":[120],"dependencies":[122],"based":[127],"on":[128,189],"relationships.":[130],"Moreover,":[131],"composite":[133,167],"constructed":[137],"integrate":[139],"features":[141],"from":[142],"different":[143,146],"layers":[144],"mapping":[147],"approaches,":[148],"it":[150],"can":[151],"well":[152],"enrich":[153],"information.":[156],"Finally,":[157],"decision-level":[159],"fusion":[160],"method":[161],"developed":[163],"combine":[165],"naive":[172],"producing":[176],"more":[178],"comprehensive":[179],"classification":[180],"result.":[181],"effectiveness":[183],"has":[186],"been":[187],"demonstrated":[188],"various":[190],"benchmark":[191],"datasets,":[192],"achieves":[195],"state-of-the-art":[196],"performance.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}