{"id":"https://openalex.org/W2558572885","doi":"https://doi.org/10.1109/kse.2016.7758033","title":"Divergence analysis by sparse neighborhood nets for detection of abnormality in image of skin","display_name":"Divergence analysis by sparse neighborhood nets for detection of abnormality in image of skin","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2558572885","doi":"https://doi.org/10.1109/kse.2016.7758033","mag":"2558572885"},"language":"en","primary_location":{"id":"doi:10.1109/kse.2016.7758033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse.2016.7758033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Eighth International Conference on Knowledge and Systems Engineering (KSE)","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/A5009794638","display_name":"Dao Nam Anh","orcid":"https://orcid.org/0000-0002-0536-8686"},"institutions":[{"id":"https://openalex.org/I121799043","display_name":"Electric Power University","ror":"https://ror.org/01p4b7n26","country_code":"VN","type":"education","lineage":["https://openalex.org/I121799043"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Dao Nam Anh","raw_affiliation_strings":["Faculty of Information Technology, Electric Power University, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Electric Power University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I121799043"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5009794638"],"corresponding_institution_ids":["https://openalex.org/I121799043"],"apc_list":null,"apc_paid":null,"fwci":0.1539,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61049684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"79","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9836000204086304,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8080200552940369},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6653075814247131},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.648174524307251},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6472734212875366},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6392457485198975},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6300213932991028},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6098740696907043},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6079482436180115},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.5855652689933777},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.5058693289756775},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.481975257396698},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4458499550819397},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.42987480759620667},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4269857704639435},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4106355905532837}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8080200552940369},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6653075814247131},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.648174524307251},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6472734212875366},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6392457485198975},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6300213932991028},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6098740696907043},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6079482436180115},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.5855652689933777},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.5058693289756775},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.481975257396698},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4458499550819397},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.42987480759620667},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4269857704639435},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4106355905532837},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kse.2016.7758033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse.2016.7758033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Eighth International Conference on Knowledge and Systems Engineering (KSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7300000190734863,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1484665381","https://openalex.org/W1581809140","https://openalex.org/W1991350669","https://openalex.org/W2003834444","https://openalex.org/W2025834121","https://openalex.org/W2043106860","https://openalex.org/W2045798786","https://openalex.org/W2057152846","https://openalex.org/W2075433722","https://openalex.org/W2082725262","https://openalex.org/W2091696547","https://openalex.org/W2100111947","https://openalex.org/W2117251230","https://openalex.org/W2158698691","https://openalex.org/W2268118031","https://openalex.org/W4236844765","https://openalex.org/W4255764808","https://openalex.org/W4300001742"],"related_works":["https://openalex.org/W4360784979","https://openalex.org/W2204605857","https://openalex.org/W1996489018","https://openalex.org/W2007664797","https://openalex.org/W2120981610","https://openalex.org/W3129669851","https://openalex.org/W2360759360","https://openalex.org/W2065064759","https://openalex.org/W3196005494","https://openalex.org/W2799097543"],"abstract_inverted_index":{"Early":[0],"detection":[1,128,141],"of":[2,6,25,29,42,52,82,108,119,122,142],"abnormality":[3],"in":[4,31,73,106],"image":[5,33,46,71],"skin":[7,56,58,143],"is":[8,68],"now":[9],"considered":[10,49],"the":[11,32,74,80,88,102,117,126,132],"crucial":[12],"contributor":[13],"for":[14,39,70,93,125,140],"successful":[15],"treatment.":[16],"We":[17],"explored":[18],"how":[19],"constructing":[20],"a":[21,37,63,136],"sparse":[22,120],"neighborhood":[23,123],"net":[24,121],"pixels":[26,124],"and":[27,60,96,111,135],"distinction":[28,127],"patches":[30,47,133],"feature":[34,66],"analysis":[35],"play":[36],"role":[38],"diagnostic":[40],"ability":[41],"lesion":[43,94],"segmentation.":[44],"Since":[45],"are":[48,90,116],"like":[50],"circumstance":[51],"many":[53],"factors":[54],"including":[55],"tone,":[57],"aberrations":[59],"lighting":[61,103],"conditions,":[62],"robust":[64],"patch-based":[65],"detector":[67],"proposed":[69],"segmentation":[72,95],"combination":[75],"with":[76,99],"post-processing":[77],"to":[78,101],"predict":[79],"presence":[81],"irregular":[83,144],"regions.":[84],"Experiments":[85],"show":[86],"that":[87],"results":[89],"very":[91],"competitive":[92],"demonstrate":[97],"robustness":[98],"respect":[100],"condition,":[104],"variations":[105],"terms":[107],"color,":[109],"texture":[110],"shape.":[112],"Our":[113],"major":[114],"contributions":[115],"application":[118],"filter":[129],"based":[130],"on":[131],"mismatch":[134],"new":[137],"efficient":[138],"algorithm":[139],"region.":[145]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}