{"id":"https://openalex.org/W2434955731","doi":"https://doi.org/10.1109/siu.2016.7495823","title":"Feature extraction for histopathological images using Convolutional Neural Network","display_name":"Feature extraction for histopathological images using Convolutional Neural Network","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2434955731","doi":"https://doi.org/10.1109/siu.2016.7495823","mag":"2434955731"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2016.7495823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2016.7495823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 24th Signal Processing and Communication Application Conference (SIU)","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/A5081983614","display_name":"Nuh Hatipo\u011flu","orcid":"https://orcid.org/0000-0002-0804-0563"},"institutions":[{"id":"https://openalex.org/I12387023","display_name":"Trakya University","ror":"https://ror.org/00xa0xn82","country_code":"TR","type":"education","lineage":["https://openalex.org/I12387023"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Nuh Hatipoglu","raw_affiliation_strings":["Bilgisayar Teknolojileri B\u00f6l\u00fcm\u00fc, Trakya \u00dcniversitesi, 22030 Edirne, Turkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar Teknolojileri B\u00f6l\u00fcm\u00fc, Trakya \u00dcniversitesi, 22030 Edirne, Turkiye","institution_ids":["https://openalex.org/I12387023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082045666","display_name":"G\u00f6khan Bilgin","orcid":"https://orcid.org/0000-0002-5532-477X"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Gokhan Bilgin","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, 34220 \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, 34220 \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.03321509,"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":"645","last_page":"648"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9825999736785889,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9603999853134155,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7964509725570679},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7819112539291382},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7533888816833496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7233105897903442},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.683998167514801},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6316606402397156},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6272053718566895},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6207423806190491},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5124974250793457},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4466802179813385},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4441826045513153},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44005680084228516},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4304526746273041},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4116900563240051},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22604066133499146}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7964509725570679},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7819112539291382},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7533888816833496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7233105897903442},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.683998167514801},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6316606402397156},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6272053718566895},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6207423806190491},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5124974250793457},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4466802179813385},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4441826045513153},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44005680084228516},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4304526746273041},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4116900563240051},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22604066133499146}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2016.7495823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2016.7495823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 24th Signal Processing and Communication Application Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W173931755","https://openalex.org/W1596986901","https://openalex.org/W1686810756","https://openalex.org/W1828658979","https://openalex.org/W1974690962","https://openalex.org/W1975103383","https://openalex.org/W1982390426","https://openalex.org/W2015861736","https://openalex.org/W2051765910","https://openalex.org/W2070238200","https://openalex.org/W2077191558","https://openalex.org/W2089580584","https://openalex.org/W2091662955","https://openalex.org/W2103243046","https://openalex.org/W2123696077","https://openalex.org/W2124155137","https://openalex.org/W2136773811","https://openalex.org/W2150341604","https://openalex.org/W2155624847","https://openalex.org/W2160738726","https://openalex.org/W2163605009","https://openalex.org/W2166934660","https://openalex.org/W2292999734","https://openalex.org/W2293399187","https://openalex.org/W2313698153","https://openalex.org/W2950858732"],"related_works":["https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3193043704","https://openalex.org/W3171520305","https://openalex.org/W1924178503","https://openalex.org/W4308716060","https://openalex.org/W4280648719","https://openalex.org/W3135126032","https://openalex.org/W3033346322","https://openalex.org/W1980222719"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"it":[3],"is":[4],"intended":[5],"to":[6],"increase":[7],"the":[8,32,60,106],"classification":[9,88],"accuracy":[10],"results":[11,108],"of":[12,37,50,64],"histopathalogical":[13,39],"images":[14],"by":[15,46,71],"evaluating":[16],"spatial":[17,57],"relations.":[18],"As":[19],"a":[20,75],"first":[21],"step,":[22],"Convolutional":[23],"Neural":[24],"Network":[25],"(CNN)":[26],"based":[27],"features":[28],"are":[29,44,69,94,100],"extracted":[30],"in":[31,56,105],"original":[33],"RGB":[34],"color":[35],"space":[36],"digital":[38],"images.":[40,61],"Training":[41],"data":[42,67],"sets":[43],"formed":[45],"selecting":[47],"equal":[48],"number":[49],"different":[51],"cellular":[52],"and":[53,82,90],"extra-cellular":[54],"structures":[55],"domain":[58],"from":[59,96],"Classification":[62],"models":[63],"each":[65],"training":[66,98],"set":[68],"obtained":[70,95],"utilizing":[72],"CNN":[73],"(as":[74],"supervised":[76,97],"classifier),":[77],"Support":[78],"Vector":[79],"Machine":[80],"(SVM)":[81],"Random":[83],"Forest":[84],"(RF)":[85],"methods.":[86],"Visual":[87],"maps":[89],"output":[91],"tables":[92],"which":[93],"methods":[99],"presented":[101],"for":[102],"comparison":[103],"purpose":[104],"experimental":[107],"section.":[109]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}