{"id":"https://openalex.org/W2895771689","doi":"https://doi.org/10.1007/978-3-030-01246-5_17","title":"Semi-supervised Deep Learning with Memory","display_name":"Semi-supervised Deep Learning with Memory","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2895771689","doi":"https://doi.org/10.1007/978-3-030-01246-5_17","mag":"2895771689"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-01246-5_17","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-01246-5_17","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5033035704","display_name":"Yanbei Chen","orcid":"https://orcid.org/0000-0002-9730-9463"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yanbei Chen","raw_affiliation_strings":["Queen Mary University of London, London, UK"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London, London, UK","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028643592","display_name":"Xiatian Zhu","orcid":"https://orcid.org/0000-0002-9284-2955"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiatian Zhu","raw_affiliation_strings":["Vision Semantics Ltd., London, UK"],"affiliations":[{"raw_affiliation_string":"Vision Semantics Ltd., London, UK","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039302902","display_name":"Shaogang Gong","orcid":"https://orcid.org/0000-0001-8156-2299"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shaogang Gong","raw_affiliation_strings":["Queen Mary University of London, London, UK"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London, London, UK","institution_ids":["https://openalex.org/I166337079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5033035704"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":11.9627,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.99082109,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"275","last_page":"291"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.8541445732116699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7619997262954712},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6391142010688782},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6233891844749451},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5816470384597778},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5805761814117432},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5286586284637451},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5083538889884949},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4835093319416046},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43897873163223267},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4207220673561096}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8541445732116699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7619997262954712},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6391142010688782},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6233891844749451},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5816470384597778},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5805761814117432},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5286586284637451},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5083538889884949},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4835093319416046},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43897873163223267},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4207220673561096},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/978-3-030-01246-5_17","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-01246-5_17","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/49609","is_oa":false,"landing_page_url":"http://qmro.qmul.ac.uk/xmlui/handle/123456789/49609","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W92894758","https://openalex.org/W830076066","https://openalex.org/W1479807131","https://openalex.org/W1630959083","https://openalex.org/W1981276685","https://openalex.org/W2037603696","https://openalex.org/W2048679005","https://openalex.org/W2061526129","https://openalex.org/W2079057609","https://openalex.org/W2107008379","https://openalex.org/W2122457239","https://openalex.org/W2136504847","https://openalex.org/W2139823104","https://openalex.org/W2151801481","https://openalex.org/W2154455818","https://openalex.org/W2159291644","https://openalex.org/W2162262658","https://openalex.org/W2187089797","https://openalex.org/W2280377497","https://openalex.org/W2293363371","https://openalex.org/W2318418736","https://openalex.org/W2335728318","https://openalex.org/W2407712691","https://openalex.org/W2411541852","https://openalex.org/W2431080869","https://openalex.org/W2432004435","https://openalex.org/W2472819217","https://openalex.org/W2520774990","https://openalex.org/W2530816535","https://openalex.org/W2581377246","https://openalex.org/W2592916831","https://openalex.org/W2621925205","https://openalex.org/W2920725015","https://openalex.org/W2949092679","https://openalex.org/W2949416428","https://openalex.org/W2951008357","https://openalex.org/W2953044442","https://openalex.org/W2953070460","https://openalex.org/W2963250052","https://openalex.org/W2963448850","https://openalex.org/W2964040467","https://openalex.org/W3037881859","https://openalex.org/W3118608800","https://openalex.org/W6638318767","https://openalex.org/W6714590955"],"related_works":["https://openalex.org/W3162567751","https://openalex.org/W4283820830","https://openalex.org/W4220686584","https://openalex.org/W4246751904","https://openalex.org/W2795261237","https://openalex.org/W2597787948","https://openalex.org/W3192794374","https://openalex.org/W4285260836","https://openalex.org/W4319309271","https://openalex.org/W3108249809"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
