{"id":"https://openalex.org/W2805155115","doi":"https://doi.org/10.1109/isbi.2018.8363640","title":"Abnormality detection using deep neural networks with robust quasi-norm autoencoding and semi-supervised learning","display_name":"Abnormality detection using deep neural networks with robust quasi-norm autoencoding and semi-supervised learning","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2805155115","doi":"https://doi.org/10.1109/isbi.2018.8363640","mag":"2805155115"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363640","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363640","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101069487","display_name":"Meet Shah","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Meet P. Shah","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027231401","display_name":"S Merchant","orcid":"https://orcid.org/0000-0002-4861-5069"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. N. Merchant","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017642893","display_name":"Suyash P. Awate","orcid":"https://orcid.org/0000-0002-4945-9539"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suyash P. Awate","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":1.0186,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.81690918,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"568","last_page":"572"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9896000027656555,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9563000202178955,"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/outlier","display_name":"Outlier","score":0.7865777015686035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7500569224357605},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7390915155410767},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.698017954826355},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6569091081619263},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.6239720582962036},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6000256538391113},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.547248125076294},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4919099807739258},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4729216694831848},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44000887870788574},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.42915624380111694},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3227998614311218}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7865777015686035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7500569224357605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7390915155410767},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.698017954826355},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6569091081619263},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.6239720582962036},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6000256538391113},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.547248125076294},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4919099807739258},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4729216694831848},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44000887870788574},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.42915624380111694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3227998614311218},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2018.8363640","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363640","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W34239198","https://openalex.org/W1543388142","https://openalex.org/W1641498739","https://openalex.org/W1686810756","https://openalex.org/W1966872876","https://openalex.org/W1970088130","https://openalex.org/W1974879849","https://openalex.org/W1999598817","https://openalex.org/W2027429916","https://openalex.org/W2074399002","https://openalex.org/W2077096052","https://openalex.org/W2078830351","https://openalex.org/W2092101233","https://openalex.org/W2103914106","https://openalex.org/W2112796928","https://openalex.org/W2127027905","https://openalex.org/W2132870739","https://openalex.org/W2134432876","https://openalex.org/W2140638323","https://openalex.org/W2181347294","https://openalex.org/W2187089797","https://openalex.org/W2204904589","https://openalex.org/W2296719434","https://openalex.org/W2464708700","https://openalex.org/W2743138268","https://openalex.org/W2752011355","https://openalex.org/W2793994880","https://openalex.org/W2963291921","https://openalex.org/W6601402213","https://openalex.org/W6632547301","https://openalex.org/W6678686966","https://openalex.org/W6685777803","https://openalex.org/W6718752587","https://openalex.org/W6743312441","https://openalex.org/W6749795623"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W2499612753","https://openalex.org/W3017266184","https://openalex.org/W3202913553","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552"],"abstract_inverted_index":{"Abnormality":[0],"detection":[1],"in":[2,72,79,137],"biomedical":[3],"images":[4],"is":[5,66],"a":[6,13,58,102,106],"one-class":[7],"classification":[8],"problem,":[9],"where":[10],"methods":[11,30],"learn":[12],"statistical":[14],"model":[15,109],"to":[16,43,68],"characterize":[17],"the":[18,26,73,111,132,135],"inlier":[19,27],"class":[20],"using":[21],"training":[22,34,74],"data":[23,35],"solely":[24],"from":[25],"class.":[28],"Typical":[29],"(i)":[31,65,98],"need":[32],"well-curated":[33],"and":[36,70,82,105,113],"(ii)":[37,83,114],"have":[38],"formulations":[39],"that":[40,64,97,128],"are":[41,77],"unable":[42],"utilize":[44],"expert":[45,86],"feedback":[46,87],"through":[47,88,101],"(a":[48],"small":[49],"amount":[50],"of)":[51],"labeled":[52,90,119],"outliers.":[53,120],"In":[54],"contrast,":[55],"we":[56],"propose":[57],"novel":[59],"deep":[60],"neural":[61],"network":[62],"framework":[63],"robust":[67],"corruption":[69],"outliers":[71],"data,":[75],"which":[76],"inevitable":[78],"real-world":[80],"deployment,":[81],"can":[84],"leverage":[85],"high-quality":[89],"data.":[91],"We":[92],"introduce":[93],"an":[94],"autoencoder":[95],"formulation":[96],"gives":[99],"robustness":[100],"non-convex":[103],"loss":[104],"heavy-tailed":[107],"distribution":[108],"on":[110,122],"residuals":[112],"enables":[115],"semi-supervised":[116],"learning":[117],"with":[118],"Results":[121],"three":[123],"large":[124],"medical":[125],"datasets":[126],"show":[127],"our":[129],"method":[130],"outperforms":[131],"state":[133],"of":[134],"art":[136],"abnormality-detection":[138],"accuracy.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
