{"id":"https://openalex.org/W2911143392","doi":"https://doi.org/10.1109/aiccsa.2018.8612826","title":"Number of Texture Unit as Feature to Breast's Disease Classification from Thermal Images","display_name":"Number of Texture Unit as Feature to Breast's Disease Classification from Thermal Images","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2911143392","doi":"https://doi.org/10.1109/aiccsa.2018.8612826","mag":"2911143392"},"language":"en","primary_location":{"id":"doi:10.1109/aiccsa.2018.8612826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiccsa.2018.8612826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA)","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/A5072686725","display_name":"Roger Resmini","orcid":"https://orcid.org/0000-0002-6068-8383"},"institutions":[{"id":"https://openalex.org/I32725510","display_name":"Universidade Federal de Mato Grosso","ror":"https://ror.org/01mqvjv41","country_code":"BR","type":"education","lineage":["https://openalex.org/I32725510"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"R. Resmini","raw_affiliation_strings":["Sistemas de Informa\u00e7\u00e3o, Universidade Federal de Mato Grosso, Rondon\u00f3polis, Brazil"],"affiliations":[{"raw_affiliation_string":"Sistemas de Informa\u00e7\u00e3o, Universidade Federal de Mato Grosso, Rondon\u00f3polis, Brazil","institution_ids":["https://openalex.org/I32725510"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103273229","display_name":"A. D.","orcid":"https://orcid.org/0009-0000-8195-7485"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"A. Araujo","raw_affiliation_strings":["Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil"],"affiliations":[{"raw_affiliation_string":"Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048172675","display_name":"Aura Conci","orcid":"https://orcid.org/0000-0003-0782-2501"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"A. Conci","raw_affiliation_strings":["Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil"],"affiliations":[{"raw_affiliation_string":"Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009561970","display_name":"Lincoln Faria da Silva","orcid":"https://orcid.org/0000-0002-3406-0146"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"L. Silva","raw_affiliation_strings":["Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil"],"affiliations":[{"raw_affiliation_string":"Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027345208","display_name":"Maira Beatriz Hern\u00e1ndez Mor\u00e1n","orcid":"https://orcid.org/0000-0002-3341-0925"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"M. Moran","raw_affiliation_strings":["Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil"],"affiliations":[{"raw_affiliation_string":"Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niter\u00f3i, Brazil","institution_ids":["https://openalex.org/I161127581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5072686725"],"corresponding_institution_ids":["https://openalex.org/I32725510"],"apc_list":null,"apc_paid":null,"fwci":0.3536,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65649896,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.9991000294685364,"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/T10862","display_name":"AI in cancer detection","score":0.9765999913215637,"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":0.9473000168800354,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7428073883056641},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7114530205726624},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6831274032592773},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.6503989696502686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6097774505615234},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5226483345031738},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.493417888879776},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.4701438248157501},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46599069237709045},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33088403940200806},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.23385804891586304},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16738620400428772},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.10797154903411865}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7428073883056641},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7114530205726624},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6831274032592773},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.6503989696502686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6097774505615234},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5226483345031738},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.493417888879776},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4701438248157501},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46599069237709045},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33088403940200806},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.23385804891586304},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16738620400428772},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.10797154903411865}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aiccsa.2018.8612826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aiccsa.2018.8612826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W36490","https://openalex.org/W121901878","https://openalex.org/W1565377632","https://openalex.org/W1570448133","https://openalex.org/W1967163031","https://openalex.org/W1984774148","https://openalex.org/W1991571876","https://openalex.org/W1993220166","https://openalex.org/W2022604464","https://openalex.org/W2044465660","https://openalex.org/W2048332782","https://openalex.org/W2059432853","https://openalex.org/W2059888210","https://openalex.org/W2124868070","https://openalex.org/W2129526018","https://openalex.org/W2133218851","https://openalex.org/W2135733203","https://openalex.org/W2154823510","https://openalex.org/W2155925556","https://openalex.org/W2166097216","https://openalex.org/W2182361439","https://openalex.org/W2397237210","https://openalex.org/W2409002119","https://openalex.org/W2482589566","https://openalex.org/W2487087946","https://openalex.org/W2980468885","https://openalex.org/W4231057059","https://openalex.org/W4255443310","https://openalex.org/W6683381688","https://openalex.org/W6685961532","https://openalex.org/W6713780271"],"related_works":["https://openalex.org/W3204374377","https://openalex.org/W1823469724","https://openalex.org/W2044270176","https://openalex.org/W2373150368","https://openalex.org/W2151854763","https://openalex.org/W2783118371","https://openalex.org/W2766950897","https://openalex.org/W2374828682","https://openalex.org/W2153116791","https://openalex.org/W2388733570"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"the":[3,6,27,30,33,48,52,59,66,78,81,88,95,99,112],"use":[4],"of":[5,8,17,22,32,80,84,91,108],"Number":[7,21],"Texture":[9,23],"Unit":[10,24],"as":[11,26],"a":[12,37,106],"feature":[13,85],"extractor":[14],"for":[15,29],"classification":[16],"breast":[18],"images.":[19],"The":[20],"served":[25],"basis":[28],"idealization":[31],"Local":[34],"Binary":[35],"Pattern":[36],"technique":[38,64],"that":[39,77],"is":[40,58],"widely":[41],"used":[42,61,98],"in":[43,65],"facial":[44],"recognition.":[45],"We":[46],"compared":[47],"proposed":[49],"strategy":[50],"with":[51],"Gray":[53],"Level":[54],"Co-occurrence":[55],"Matrix":[56],"which":[57],"most":[60],"texture":[62],"analysis":[63],"literature.":[67],"With":[68],"this":[69],"work":[70],"we":[71,97],"have":[72],"been":[73],"able":[74],"to":[75],"show":[76],"combination":[79],"two":[82],"techniques":[83],"extraction":[86],"improves":[87],"final":[89],"result":[90,107],"classification.":[92],"To":[93],"perform":[94],"tests":[96],"Support":[100],"Vectors":[101],"Machine":[102],"classifier":[103],"and":[104],"obtained":[105],"96.15%":[109],"Area":[110],"Under":[111],"Curve":[113],"(Receiver":[114],"Operating":[115],"Characteristic":[116],"Curve).":[117]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
