{"id":"https://openalex.org/W2939459869","doi":"https://doi.org/10.1109/fskd.2018.8686904","title":"Deep Kernel Learning with Application to Medical Image Annotation","display_name":"Deep Kernel Learning with Application to Medical Image Annotation","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2939459869","doi":"https://doi.org/10.1109/fskd.2018.8686904","mag":"2939459869"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2018.8686904","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2018.8686904","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","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/A5002570462","display_name":"Gang Zhang","orcid":"https://orcid.org/0000-0002-3998-4663"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Zhang","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","School of Automation, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101808358","display_name":"Ling Zhong","orcid":"https://orcid.org/0000-0002-0196-4587"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Zhong","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","School of Automation, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037292846","display_name":"Ming Xiao","orcid":"https://orcid.org/0000-0002-5407-0835"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Xiao","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","School of Automation, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101578650","display_name":"Yonghui Huang","orcid":"https://orcid.org/0000-0002-7858-0952"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong-Hui Huang","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","School of Automation, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002570462"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.1045,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49621945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1346","last_page":"1352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9972000122070312,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9970999956130981,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7220552563667297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7173660397529602},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.6892606616020203},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6702632904052734},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.6380183100700378},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.5940815210342407},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.5525797605514526},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5359184741973877},{"id":"https://openalex.org/keywords/string-kernel","display_name":"String kernel","score":0.5336129665374756},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.522602379322052},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.5058512687683105},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4915851056575775},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.48075056076049805},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.4753192067146301},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.428469717502594},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.4140644967556},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.40927866101264954},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14853382110595703}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7220552563667297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7173660397529602},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.6892606616020203},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6702632904052734},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.6380183100700378},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.5940815210342407},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.5525797605514526},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5359184741973877},{"id":"https://openalex.org/C55851704","wikidata":"https://www.wikidata.org/wiki/Q7623983","display_name":"String kernel","level":5,"score":0.5336129665374756},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.522602379322052},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.5058512687683105},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4915851056575775},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.48075056076049805},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.4753192067146301},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.428469717502594},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.4140644967556},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.40927866101264954},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14853382110595703},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2018.8686904","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2018.8686904","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W134688180","https://openalex.org/W1506806321","https://openalex.org/W1560724230","https://openalex.org/W1613249581","https://openalex.org/W1988581925","https://openalex.org/W2027266161","https://openalex.org/W2095705004","https://openalex.org/W2101048999","https://openalex.org/W2103243046","https://openalex.org/W2109743529","https://openalex.org/W2117499988","https://openalex.org/W2135197770","https://openalex.org/W2138857742","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2418306335","https://openalex.org/W2558026684","https://openalex.org/W2561964848","https://openalex.org/W2572546447","https://openalex.org/W2587063199","https://openalex.org/W2666784499","https://openalex.org/W2744130673","https://openalex.org/W2755446223","https://openalex.org/W2756270667","https://openalex.org/W2763160469","https://openalex.org/W2772412867","https://openalex.org/W2777186991","https://openalex.org/W2783388698","https://openalex.org/W2790182932","https://openalex.org/W2790701475","https://openalex.org/W2791460829","https://openalex.org/W2793994880","https://openalex.org/W2964074409","https://openalex.org/W2964211601","https://openalex.org/W3101183984","https://openalex.org/W3144619878","https://openalex.org/W6636456564","https://openalex.org/W6674330103","https://openalex.org/W6676602786","https://openalex.org/W6677604277","https://openalex.org/W6680300913","https://openalex.org/W6684191040","https://openalex.org/W6685380521","https://openalex.org/W7058071925"],"related_works":["https://openalex.org/W3013206934","https://openalex.org/W4291669689","https://openalex.org/W2071590642","https://openalex.org/W1969447452","https://openalex.org/W2806943235","https://openalex.org/W1976730005","https://openalex.org/W2141199622","https://openalex.org/W2898882859","https://openalex.org/W2055608878","https://openalex.org/W2001173190"],"abstract_inverted_index":{"Deep":[0],"learning":[1,9,77,81,85],"methods":[2],"achieve":[3,48],"significant":[4],"success":[5],"in":[6],"many":[7],"machine":[8],"problems.":[10],"By":[11],"increasing":[12],"the":[13,64,84,92,107,119,133,146],"model":[14,17,65,89],"depth,":[15],"deep":[16,76,88,137],"can":[18,47],"learn":[19,68],"very":[20],"complex":[21],"functions":[22],"from":[23,32],"large":[24],"scale":[25],"dataset.":[26],"Kernel":[27,45],"method":[28,46,105,142],"induce":[29],"a":[30,42,75,96,110,115,122],"mapping":[31],"input":[33],"space":[34,40],"to":[35,90,132,145,158],"certain":[36],"high":[37],"dimension":[38],"feature":[39],"via":[41],"kernel":[43,59,71,101,111],"function.":[44],"good":[49],"generalization":[50],"performance":[51,120],"even":[52],"with":[53,125,156],"small":[54],"training":[55,134],"datasets.":[56],"A":[57],"proper":[58],"function":[60],"would":[61],"dramatically":[62],"affect":[63],"performance.":[66],"To":[67],"an":[69],"effective":[70],"function,":[72],"we":[73],"propose":[74],"based":[78,117],"multiple-layer":[79],"multiple-kernel":[80],"algorithm,":[82],"utilizing":[83],"ability":[86],"of":[87,95,99,109,121,136,148],"find":[91],"best":[93],"combination":[94],"base":[97],"set":[98],"structured":[100],"functions.":[102],"The":[103,140],"proposed":[104,141],"updates":[106],"weights":[108],"network":[112],"by":[113],"optimizing":[114],"metric":[116],"on":[118],"SVM":[123],"classifier":[124],"current":[126,159],"learned":[127],"kernels,":[128],"which":[129],"is":[130,143],"similar":[131],"procedure":[135],"neural":[138],"network.":[139],"applied":[144],"problem":[147],"medical":[149],"image":[150],"annotation":[151],"and":[152],"achieves":[153],"superior":[154],"results":[155],"comparison":[157],"state-of-the-art":[160],"methods.":[161]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
