{"id":"https://openalex.org/W3038286218","doi":"https://doi.org/10.1109/access.2020.3007337","title":"Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability","display_name":"Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3038286218","doi":"https://doi.org/10.1109/access.2020.3007337","mag":"3038286218"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3007337","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3007337","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09133368.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09133368.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032669664","display_name":"Mohammadreza Amirian","orcid":"https://orcid.org/0000-0003-0047-6802"},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]},{"id":"https://openalex.org/I858936495","display_name":"ZHAW Zurich University of Applied Sciences","ror":"https://ror.org/05pmsvm27","country_code":"CH","type":"education","lineage":["https://openalex.org/I858936495"]}],"countries":["CH","DE"],"is_corresponding":true,"raw_author_name":"Mohammadreza Amirian","raw_affiliation_strings":["Institute of Applied Information Technology, Zurich University of Applied Sciences, Winterthur, Switzerland","Institute of Neural Information Processing, Ulm University, Ulm, Germany","Institute of Neural Information Processing, Ulm University, 89081 Ulm, Germany","Institute of Applied Information Technology, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland"],"affiliations":[{"raw_affiliation_string":"Institute of Applied Information Technology, Zurich University of Applied Sciences, Winterthur, Switzerland","institution_ids":["https://openalex.org/I858936495"]},{"raw_affiliation_string":"Institute of Neural Information Processing, Ulm University, Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]},{"raw_affiliation_string":"Institute of Neural Information Processing, Ulm University, 89081 Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]},{"raw_affiliation_string":"Institute of Applied Information Technology, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland","institution_ids":["https://openalex.org/I858936495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078096723","display_name":"Friedhelm Schwenker","orcid":"https://orcid.org/0000-0001-5118-0812"},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friedhelm Schwenker","raw_affiliation_strings":["Institute of Neural Information Processing, Ulm University, Ulm, Germany","Institute of Neural Information Processing, Ulm University, 89081 Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Neural Information Processing, Ulm University, Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]},{"raw_affiliation_string":"Institute of Neural Information Processing, Ulm University, 89081 Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032669664"],"corresponding_institution_ids":["https://openalex.org/I196349391","https://openalex.org/I858936495"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1467,"currency":"EUR","value_usd":1582},"fwci":2.0605,"has_fulltext":true,"cited_by_count":38,"citation_normalized_percentile":{"value":0.89160752,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"123087","last_page":"123097"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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":0.9988999962806702,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7990251779556274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7945319414138794},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7790446877479553},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6901319622993469},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.6676650047302246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5405063033103943},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5375151038169861},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5054361820220947},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4946865737438202},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4713149666786194},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4390280544757843},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.4285159707069397},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.425433874130249}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7990251779556274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7945319414138794},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7790446877479553},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6901319622993469},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.6676650047302246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5405063033103943},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5375151038169861},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5054361820220947},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4946865737438202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4713149666786194},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4390280544757843},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.4285159707069397},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.425433874130249},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/access.2020.3007337","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3007337","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09133368.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2208.11401","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.11401","pdf_url":"https://arxiv.org/pdf/2208.11401","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"},{"id":"pmh:oai:digitalcollection.zhaw.ch:11475/26284","is_oa":true,"landing_page_url":"https://hdl.handle.net/11475/26284","pdf_url":null,"source":{"id":"https://openalex.org/S4306401810","display_name":"Z\u00fcrcher Hochschule f\u00fcr Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200744771","host_organization_name":"ZHAW Zurich University of Applied Sciences","host_organization_lineage":["https://openalex.org/I200744771"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:5bc4be2688494bdd8f28c1b5eb170f46","is_oa":true,"landing_page_url":"https://doaj.org/article/5bc4be2688494bdd8f28c1b5eb170f46","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 123087-123097 (2020)","raw_type":"article"},{"id":"pmh:oai:oparu.uni-ulm.de:123456789/34160","is_oa":true,"landing_page_url":"http://nbn-resolving.de/urn:nbn:de:bsz:289-oparu-34160-6","pdf_url":null,"source":{"id":"https://openalex.org/S4306400353","display_name":"OPen Access Repositorium der Universit\u00e4t Ulm (OPARU) (Ulm University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I196349391","host_organization_name":"Universit\u00e4t Ulm","host_organization_lineage":["https://openalex.org/I196349391"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.18725/oparu-34098","is_oa":true,"landing_page_url":"https://doi.org/10.18725/oparu-34098","pdf_url":null,"source":{"id":"https://openalex.org/S7407052964","display_name":"Universit\u00e4t Ulm, Kommunikations- und Informationszentrum (kiz)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3007337","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3007337","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09133368.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3038286218.pdf","grobid_xml":"https://content.openalex.org/works/W3038286218.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1572940464","https://openalex.org/W1829366209","https://openalex.org/W1846799578","https://openalex.org/W1916279783","https://openalex.org/W1958023451","https://openalex.org/W1963581687","https://openalex.org/W1974511160","https://openalex.org/W1975100741","https://openalex.org/W1977295328","https://openalex.org/W1996118086","https://openalex.org/W1998242011","https://openalex.org/W2078933500","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2114515835","https://openalex.org/W2117154949","https://openalex.org/W2117539524","https://openalex.org/W2118587067","https://openalex.org/W2143956139","https://openalex.org/W2149489931","https://openalex.org/W2158247472","https://openalex.org/W2171277043","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2512771069","https://openalex.org/W2533598788","https://openalex.org/W2556522401","https://openalex.org/W2783165089","https://openalex.org/W2899459625","https://openalex.org/W2908510526","https://openalex.org/W2910603373","https://openalex.org/W2915640454","https://openalex.org/W2921358543","https://openalex.org/W2949736877","https://openalex.org/W2950703532","https://openalex.org/W2955425717","https://openalex.org/W2963026686","https://openalex.org/W2963775347","https://openalex.org/W2963815651","https://openalex.org/W2963988212","https://openalex.org/W2997274137","https://openalex.org/W3098744844","https://openalex.org/W3118608800","https://openalex.org/W6600609147","https://openalex.org/W6638677478","https://openalex.org/W6677328822","https://openalex.org/W6730169791","https://openalex.org/W6757817989","https://openalex.org/W6762718338","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4388685194","https://openalex.org/W2157934879","https://openalex.org/W4234515837","https://openalex.org/W2370830768"],"abstract_inverted_index":{"Radial":[0],"basis":[1],"function":[2,77],"neural":[3,41],"networks":[4,42,59],"(RBFs)":[5],"are":[6],"prime":[7],"candidates":[8],"for":[9,84],"pattern":[10],"classification":[11],"and":[12,14,35,72,102,105,144],"regression":[13],"have":[15,26],"been":[16,28],"used":[17],"extensively":[18],"in":[19],"classical":[20],"machine":[21],"learning":[22,33,94],"applications.":[23],"However,":[24],"RBFs":[25,91,137],"not":[27],"integrated":[29],"into":[30],"contemporary":[31],"deep":[32],"research":[34],"computer":[36,150],"vision":[37,81,151],"using":[38,112],"conventional":[39],"convolutional":[40],"(CNNs)":[43],"due":[44],"to":[45,78,100,138],"their":[46],"lack":[47],"of":[48,65,90,95,118,130,141],"adaptability":[49],"with":[50],"modern":[51,80],"architectures.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56,109,134],"adapt":[57],"RBF":[58,114],"as":[60],"a":[61,74,96,139],"classifier":[62,115],"on":[63,116,148],"top":[64,117],"CNNs":[66],"by":[67],"modifying":[68],"the":[69,93,127,131,146],"training":[70],"process":[71,129],"introducing":[73],"new":[75,123],"activation":[76],"train":[79],"architectures":[82,143],"end-to-end":[83],"image":[85],"classification.":[86],"The":[87],"specific":[88],"architecture":[89,121],"enables":[92],"similarity":[97],"distance":[98],"metric":[99],"compare":[101],"find":[103],"similar":[104],"dissimilar":[106],"images.":[107],"Furthermore,":[108],"demonstrate":[110],"that":[111],"an":[113],"any":[119],"CNN":[120,142],"provides":[122],"human-interpretable":[124],"insights":[125],"about":[126],"decision-making":[128],"models.":[132],"Finally,":[133],"successfully":[135],"apply":[136],"range":[140],"evaluate":[145],"results":[147],"benchmark":[149],"datasets.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2020-07-10T00:00:00"}