{"id":"https://openalex.org/W2806067588","doi":"https://doi.org/10.1109/isbi.2018.8363771","title":"A stacked deep autoencoder model for biomedical figure classification","display_name":"A stacked deep autoencoder model for biomedical figure classification","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2806067588","doi":"https://doi.org/10.1109/isbi.2018.8363771","mag":"2806067588"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363771","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/A5015102986","display_name":"Ibrahim Almakky","orcid":"https://orcid.org/0009-0008-8802-7107"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ibrahim Almakky","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076935774","display_name":"Vasile Palade","orcid":"https://orcid.org/0000-0002-6768-8394"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Vasile Palade","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109989136","display_name":"Yih-Ling Hedley","orcid":null},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yih-Ling Hedley","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045393106","display_name":"Jianhua Yang","orcid":"https://orcid.org/0000-0003-1354-9230"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jianhua Yang","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I73417466"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"37","issue":null,"first_page":"1134","last_page":"1138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9969000220298767,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9969000220298767,"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/T10862","display_name":"AI in cancer detection","score":0.991100013256073,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9771000146865845,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9308210611343384},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7770835161209106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7616746425628662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7102072238922119},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6931941509246826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5593558549880981},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4945788085460663},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4714188277721405},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.448426753282547},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3407987952232361}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9308210611343384},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7770835161209106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7616746425628662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7102072238922119},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6931941509246826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5593558549880981},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4945788085460663},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4714188277721405},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.448426753282547},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3407987952232361},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2018.8363771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363771","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1970933811","https://openalex.org/W2032235169","https://openalex.org/W2032509980","https://openalex.org/W2059106541","https://openalex.org/W2098146557","https://openalex.org/W2100495367","https://openalex.org/W2110798204","https://openalex.org/W2124973181","https://openalex.org/W2126687787","https://openalex.org/W2168074160","https://openalex.org/W2194775991","https://openalex.org/W2248620004","https://openalex.org/W2294218214","https://openalex.org/W2509752429","https://openalex.org/W2559785631","https://openalex.org/W2576726837","https://openalex.org/W2731119740","https://openalex.org/W2981020605","https://openalex.org/W6638667902","https://openalex.org/W6676481782","https://openalex.org/W6732478121"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"Figures":[0],"in":[1,64,165],"biomedical":[2,26,44,67],"research":[3],"papers":[4],"are":[5],"a":[6,57,127],"significant":[7],"source":[8],"of":[9,19,135,140],"vital":[10],"information":[11],"surrounding":[12],"the":[13,20,30,47,51,65,71,75,80,92,117,138,141,145,153,159,162,166,170],"experimental":[14],"settings":[15],"and":[16,28,100],"results.":[17],"One":[18],"most":[21],"important":[22],"steps":[23],"towards":[24],"mining":[25],"figures":[27,45],"reducing":[29],"vast":[31],"search":[32],"space":[33],"is":[34,46,88,110],"figure":[35,142],"classification.":[36],"A":[37,83],"challenge":[38],"that":[39,124,152],"presents":[40,56],"itself":[41],"when":[42],"classifying":[43],"huge":[48],"imbalance":[49,63],"between":[50],"devised":[52],"classes.":[53],"This":[54],"paper":[55],"novel":[58],"method":[59,155],"to":[60,90,102,112],"overcome":[61],"this":[62],"available":[66],"figures,":[68,93],"by":[69,96,143],"improving":[70,79],"prediction":[72],"accuracy":[73,160],"on":[74,161],"small":[76],"classes,":[77],"hence":[78],"overall":[81,171],"accuracy.":[82,172],"stacked":[84],"deep":[85],"autoencoder":[86],"model":[87],"trained":[89],"reconstruct":[91],"then":[94],"trimmed,":[95],"removing":[97],"its":[98],"decoder,":[99],"used":[101],"automatically":[103],"extract":[104],"visual":[105],"features.":[106],"The":[107,133,148],"remaining":[108],"encoder":[109,121],"fine-tuned":[111],"classify":[113],"each":[114,120],"class":[115,139],"against":[116],"rest,":[118],"with":[119],"generating":[122],"features":[123],"feed":[125],"into":[126],"one-vs-all":[128],"support":[129],"vector":[130],"machine":[131],"(SVM).":[132],"ensemble":[134],"SVMs":[136],"determines":[137],"taking":[144],"highest":[146],"probability.":[147],"obtained":[149],"results":[150],"show":[151],"proposed":[154],"improves":[156],"not":[157],"only":[158],"smaller":[163],"classes":[164],"taxonomy,":[167],"but":[168],"also":[169]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
