{"id":"https://openalex.org/W3034104766","doi":"https://doi.org/10.1145/3372278.3390720","title":"System Fusion with Deep Ensembles","display_name":"System Fusion with Deep Ensembles","publication_year":2020,"publication_date":"2020-06-02","ids":{"openalex":"https://openalex.org/W3034104766","doi":"https://doi.org/10.1145/3372278.3390720","mag":"3034104766"},"language":"en","primary_location":{"id":"doi:10.1145/3372278.3390720","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372278.3390720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Multimedia Retrieval","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/A5062563309","display_name":"Liviu\u2013Daniel Stefan","orcid":"https://orcid.org/0000-0001-9174-3923"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Liviu-Daniel \u015etefan","raw_affiliation_strings":["University Politehnica of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026839903","display_name":"Mihai Gabriel Constantin","orcid":"https://orcid.org/0000-0002-2312-6672"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Mihai Gabriel Constantin","raw_affiliation_strings":["University Politehnica of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051234459","display_name":"Bogdan Ionescu","orcid":"https://orcid.org/0000-0003-4112-5769"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Bogdan Ionescu","raw_affiliation_strings":["University Politehnica of Bucharest, Bucharest, Romania"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest, Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062563309"],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67868713,"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":"256","last_page":"260"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9990000128746033,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9973999857902527,"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/computer-science","display_name":"Computer science","score":0.8195126056671143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7387338876724243},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.729116678237915},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6764107942581177},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6698931455612183},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6329437494277954},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.6201575994491577},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6060233116149902},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6048280000686646},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4174593389034271},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34779083728790283}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8195126056671143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7387338876724243},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.729116678237915},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6764107942581177},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6698931455612183},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6329437494277954},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6201575994491577},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6060233116149902},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6048280000686646},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4174593389034271},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34779083728790283},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3372278.3390720","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372278.3390720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1988790447","https://openalex.org/W2005825070","https://openalex.org/W2097117768","https://openalex.org/W2146254396","https://openalex.org/W2158275940","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2220384803","https://openalex.org/W2397200767","https://openalex.org/W2461528596","https://openalex.org/W2552478800","https://openalex.org/W2557449848","https://openalex.org/W2573570971","https://openalex.org/W2585528949","https://openalex.org/W2602516395","https://openalex.org/W2772584248","https://openalex.org/W2773552330","https://openalex.org/W2789758093","https://openalex.org/W2802022891","https://openalex.org/W2807727695","https://openalex.org/W2897642955","https://openalex.org/W2915590943","https://openalex.org/W2949382160","https://openalex.org/W2963430540","https://openalex.org/W2963744840","https://openalex.org/W2964024144","https://openalex.org/W2990604978","https://openalex.org/W2990847174","https://openalex.org/W3018631665","https://openalex.org/W3102058420","https://openalex.org/W3152294918"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3124943098","https://openalex.org/W4308112567"],"abstract_inverted_index":{"Deep":[0],"neural":[1,51],"networks":[2],"(DNNs)":[3],"are":[4],"universal":[5],"estimators":[6],"that":[7,88],"have":[8],"achieved":[9],"state-of-the-art":[10,110],"performance":[11],"in":[12],"a":[13,37,113],"broad":[14],"spectrum":[15],"of":[16,26,39,64,71,92,97],"classification":[17],"tasks,":[18],"opening":[19],"new":[20],"perspectives":[21,91],"for":[22,43],"many":[23],"applications.":[24],"One":[25],"them":[27],"is":[28],"addressing":[29],"ensemble":[30,44],"learning.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,79],"introduce":[36],"set":[38],"deep":[40],"learning":[41,45],"techniques":[42],"with":[46],"dense,":[47],"attention,":[48],"and":[49,59,102],"convolutional":[50],"network":[52],"layers.":[53],"Our":[54],"approach":[55,82,106],"automatically":[56],"discovers":[57],"patterns":[58],"correlations":[60],"between":[61],"the":[62,69,94,108],"decisions":[63],"individual":[65],"classifiers,":[66],"therefore,":[67],"alleviating":[68],"difficulty":[70],"building":[72],"such":[73],"architectures.":[74],"To":[75],"assess":[76],"its":[77],"robustness,":[78],"evaluate":[80],"our":[81],"on":[83],"two":[84],"complex":[85],"data":[86],"sets":[87],"target":[89],"different":[90],"predicting":[93],"user":[95],"perception":[96],"multimedia":[98],"data,":[99],"i.e.,":[100],"interestingness":[101],"violence.":[103],"The":[104],"proposed":[105],"outperforms":[107],"existing":[109],"algorithms":[111],"by":[112],"large":[114],"margin.":[115]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
