{"id":"https://openalex.org/W4387652602","doi":"https://doi.org/10.1080/21681163.2023.2266048","title":"Hybrid generative model for grading the severity of diabetic retinopathy images","display_name":"Hybrid generative model for grading the severity of diabetic retinopathy images","publication_year":2023,"publication_date":"2023-10-15","ids":{"openalex":"https://openalex.org/W4387652602","doi":"https://doi.org/10.1080/21681163.2023.2266048"},"language":"en","primary_location":{"id":"doi:10.1080/21681163.2023.2266048","is_oa":false,"landing_page_url":"https://doi.org/10.1080/21681163.2023.2266048","pdf_url":null,"source":{"id":"https://openalex.org/S2764763012","display_name":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","issn_l":"2168-1163","issn":["2168-1163","2168-1171"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5101709096","display_name":"R. Bhuvaneswari","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Bhuvaneswari","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Chennai, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002699734","display_name":"M. Diviya","orcid":"https://orcid.org/0000-0002-4166-9961"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"M. Diviya","raw_affiliation_strings":["Department of Computer Science and Engineering, Amrita School of Computing, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Amrita School of Computing, Chennai, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109119150","display_name":"M. Subramanian","orcid":null},"institutions":[{"id":"https://openalex.org/I4387154592","display_name":"St. Joseph\u2019s College of Engineering","ror":"https://ror.org/01g3pby21","country_code":null,"type":"education","lineage":["https://openalex.org/I4387154592"]},{"id":"https://openalex.org/I4210101093","display_name":"St. Joseph's Institute of Technology","ror":"https://ror.org/012npkr10","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210101093"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Subramanian","raw_affiliation_strings":["Department of Mechanical Engineering, St.Joseph\u2019s College of Engineering, Chennai, India","Department of Mechanical Engineering, St.Joseph's College of Engineering, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, St.Joseph\u2019s College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I4210101093","https://openalex.org/I4387154592"]},{"raw_affiliation_string":"Department of Mechanical Engineering, St.Joseph's College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I4210101093","https://openalex.org/I4387154592"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092647371","display_name":"Ramya Maranan","orcid":"https://orcid.org/0009-0007-8772-961X"},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramya Maranan","raw_affiliation_strings":["Department of Research and Innovation, Saveetha School of Engineering, SIMATS, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Research and Innovation, Saveetha School of Engineering, SIMATS, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010886857","display_name":"R. Josphineleela","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R Josphineleela","raw_affiliation_strings":["Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5002699734"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":1.6521,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84431758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"11","issue":"7","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":1.0,"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/T11438","display_name":"Retinal Imaging and Analysis","score":1.0,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9894999861717224,"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":0.7543944120407104},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6768158078193665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6468936204910278},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6407245397567749},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6322522163391113},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6024832725524902},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.5101266503334045},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5048742890357971},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.48939409852027893},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48468759655952454},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4483835697174072},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.4466603994369507},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.44444090127944946},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4161912798881531},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22051730751991272},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14405250549316406},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.1046743392944336},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07948184013366699}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7543944120407104},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6768158078193665},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6468936204910278},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407245397567749},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6322522163391113},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6024832725524902},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5101266503334045},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5048742890357971},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.48939409852027893},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48468759655952454},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4483835697174072},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.4466603994369507},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.44444090127944946},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4161912798881531},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22051730751991272},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14405250549316406},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.1046743392944336},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07948184013366699},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/21681163.2023.2266048","is_oa":false,"landing_page_url":"https://doi.org/10.1080/21681163.2023.2266048","pdf_url":null,"source":{"id":"https://openalex.org/S2764763012","display_name":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","issn_l":"2168-1163","issn":["2168-1163","2168-1171"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W127780887","https://openalex.org/W1969496006","https://openalex.org/W1982168774","https://openalex.org/W1982890488","https://openalex.org/W2114063873","https://openalex.org/W2123215356","https://openalex.org/W2469657297","https://openalex.org/W2530895041","https://openalex.org/W2780565149","https://openalex.org/W2888519944","https://openalex.org/W2891188263","https://openalex.org/W2906933145","https://openalex.org/W2914884512","https://openalex.org/W2946233353","https://openalex.org/W2960092041","https://openalex.org/W2964291324","https://openalex.org/W2969771517","https://openalex.org/W2979927758","https://openalex.org/W3002425258","https://openalex.org/W3004921770","https://openalex.org/W3009545797","https://openalex.org/W3011462389","https://openalex.org/W3034436104","https://openalex.org/W3035993151","https://openalex.org/W3036616390","https://openalex.org/W3048802372","https://openalex.org/W3085574514","https://openalex.org/W3152113692","https://openalex.org/W3198286218","https://openalex.org/W3204146347","https://openalex.org/W3205018926","https://openalex.org/W3206815816","https://openalex.org/W4205213185","https://openalex.org/W4205416183","https://openalex.org/W4212945932","https://openalex.org/W4212984122","https://openalex.org/W4224930827","https://openalex.org/W4225709903","https://openalex.org/W4236647340","https://openalex.org/W4244371405","https://openalex.org/W4280630144","https://openalex.org/W4281772828","https://openalex.org/W4287099037","https://openalex.org/W4289938749","https://openalex.org/W4296473473","https://openalex.org/W4306790045","https://openalex.org/W4315977407","https://openalex.org/W4318219815","https://openalex.org/W4320000218","https://openalex.org/W4327809132","https://openalex.org/W4362590227","https://openalex.org/W4367018081","https://openalex.org/W4382138749","https://openalex.org/W6960068798"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W4247136043","https://openalex.org/W4312407344","https://openalex.org/W4384115502","https://openalex.org/W4226258012","https://openalex.org/W2075383893"],"abstract_inverted_index":{"ABSTRACTOne":[0],"of":[1,28,41,44,64,125,162,166,187,209,232,259,270,276,325,338,349,355,429,448,484,491,504,519,535,629,643,649,669,692,719,725],"the":[2,18,22,26,32,42,52,65,85,106,115,151,163,170,179,185,188,214,229,233,243,256,274,312,335,353,427,482,502,516,520,574,586,627,641,667],"common":[3],"eye":[4],"conditions":[5],"affecting":[6],"patients":[7],"with":[8,25,191,221,255,334],"diabetes":[9],"is":[10,15,250,329,415,476,634,665],"diabetic":[11],"retinopathy":[12],"(DR).":[13],"It":[14],"characterised":[16],"by":[17,178,213],"progressive":[19],"impairment":[20],"to":[21,95,109,149,155,451,558,563,576,585],"blood":[23],"vessels":[24],"increase":[27],"glucose":[29],"level":[30],"in":[31,78,136,273,322,352,392,402,409,426,441,481,494,514,540,604,616,626,640,658,666,732],"blood.":[33],"The":[34],"grading":[35],"efficiency":[36],"still":[37],"finds":[38],"challenging":[39],"because":[40],"existence":[43],"intra-class":[45],"variations":[46],"and":[47,128,132,147,157,194,287,290,303,366,369,378,397,406,411,432,463,471,486,506,529,542,546,549,567,583,589,614,632,660,678,694,748],"imbalanced":[48],"data":[49,139],"distributions":[50],"on":[51,236,284,294,363,460,581],"retinal":[53,67],"images.":[54,68],"Traditional":[55],"machine":[56,301,376,467],"learning":[57,302,305,377,380],"techniques":[58],"utilise":[59],"hand-engineered":[60],"features":[61,108,167],"for":[62,101,168,306,381,500,703,727,741],"classification":[63,76],"affected":[66],"As":[69],"convolutional":[70],"neural":[71],"network":[72],"produces":[73],"better":[74],"image":[75,307,382,469],"accuracy":[77,192],"many":[79,282,361],"medical":[80],"images,":[81],"this":[82],"work":[83,523,572],"utilises":[84],"CNN-based":[86],"feature":[87,91,199],"extraction":[88],"method.":[89],"This":[90],"has":[92,133,218,267,279,346,358,573,594,607,620,652,683,722,737],"been":[93,219],"used":[94],"build":[96],"Gaussian":[97,116],"mixture":[98,117,124,203],"model":[99,118,153,190,204],"(GMM)":[100],"each":[102],"class":[103],"that":[104],"maps":[105],"CNN":[107],"log-likelihood":[110],"dimensional":[111],"vector":[112,174,201],"spaces.":[113],"Since":[114],"can":[119],"be":[120],"realised":[121],"as":[122,437,637,729],"a":[123,159,292,389,498,511,578,638,685,730],"both":[126],"parametric":[127],"nonparametric":[129],"density":[130],"models":[131],"their":[134,533,551],"flexibility":[135],"capturing":[137],"different":[138],"distributions,":[140],"probabilistic":[141],"outputs,":[142],"interpretability,":[143],"efficient":[144],"parameter":[145],"estimation,":[146],"robustness":[148],"outliers,":[150],"proposed":[152,189],"aimed":[154],"obtain":[156],"provide":[158],"smooth":[160],"approximation":[161],"underlying":[164],"distribution":[165],"training":[169],"model.":[171],"Then":[172],"these":[173],"spaces":[175],"are":[176,538],"trained":[177],"SVM":[180],"classifier.":[181],"Experimental":[182],"results":[183],"illustrate":[184],"efficacy":[186],"86.3%":[193],"89.1%,":[195],"respectively.KEYWORDS:":[196],"Retinal":[197],"imagesCNN":[198],"extractionsupport":[200],"machineGaussian":[202],"Disclosure":[205],"statementNo":[206],"potential":[207,575],"conflict":[208],"interest":[210],"was":[211],"reported":[212],"authors.Correction":[215],"StatementThis":[216],"article":[217],"republished":[220],"minor":[222],"changes.":[223],"These":[224],"changes":[225],"do":[226],"not":[227],"impact":[228,580],"academic":[230,588],"content":[231],"article.Additional":[234],"informationNotes":[235],"contributorsR.":[237],"BhuvaneswariR.":[238],"Bhuvaneswari":[239],"(Member,":[240],"IEEE)":[241],"received":[242,311,388,595,684,695,723,738],"Ph.D.":[244],"degree":[245,315,391,419],"from":[246,316,395,420,600,689,699,709,716,751,758],"Anna":[247,317,421,452],"University.":[248,318,618],"She":[249,266,278,328,345,357,606,619,651,682,711,736],"currently":[251,330,635],"an":[252,331,438,477,743],"Assistant":[253,332],"Professor":[254,333,639,687],"Amrita":[257,261,336,340],"School":[258,337,490],"Computing,":[260,339],"Vishwa":[262,341],"Vidyapeetham,":[263,342],"Chennai,":[264,343,423,454,495],"India.":[265,344,456,496],"18":[268],"years":[269,348],"teaching":[271,350],"experience":[272,351,625],"field":[275,354,428,628,668],"engineering.":[277,356,433],"authored":[280,359],"over":[281,360],"publications":[283,362],"international":[285,288,364,367,661],"journals":[286,365],"conferences":[289,368],"co-authored":[291],"book":[293,370],"computer":[295,403],"graphics.":[296],"Her":[297,372,663],"research":[298,373,458,517,528,559,664],"interests":[299,374],"include":[300,375],"deep":[304,379],"processing":[308,384,470],"applications.M.":[309,385],"DiviyaM.Diviya":[310],"M.E":[313],".":[314],"Currently":[319],"pursuing":[320,416],"Ph.D":[321],"Vellore":[323],"Institute":[324,648],"Technology,":[326],"Chennai.":[327],"7":[347],"chapters.":[371],"processing,text":[383],"SubramanianSubramanian":[386],"M":[387],"BE":[390],"Mechanical":[393],"Engineering":[394],"2008,":[396],"he":[398,435],"obtained":[399],"ME":[400],"degrees":[401],"aided":[404],"design":[405,408,755],"engineering":[407,443],"2011":[410],"2013,":[412],"respectively.":[413],"He":[414],"his":[417],"PhD":[418],"University,":[422,453,602,705],"Tamilnadu,":[424,455],"India":[425,603,693],"material":[430,461],"science":[431,462,613],"Currently,":[434],"serves":[436],"assistant":[439],"professor":[440],"mechanical":[442],"department":[444,642],"at":[445,488,646],"St.Joseph's":[446],"College":[447],"Engineering,":[449,492],"affiliated":[450],"His":[457],"focusses":[459],"metallurgy,":[464],"machining":[465],"science,":[466],"learning,":[468],"optimization":[472],"techniques.Ramya":[473],"MarananRamya":[474],"Maranan":[475],"accomplished":[478],"researcher":[479],"working":[480,636],"Department":[483],"Research":[485],"Innovation":[487,753],"Saveetha":[489],"SIMATS":[493],"With":[497],"passion":[499],"pushing":[501],"boundaries":[503],"knowledge":[505],"driving":[507],"innovation,":[508],"Ramya":[509],"plays":[510],"vital":[512],"role":[513],"advancing":[515,564],"activities":[518,531],"institution.":[521],"Ramya's":[522,556],"primarily":[524],"revolves":[525],"around":[526],"conducting":[527],"development":[530],"within":[532],"area":[534],"specialization.":[536],"They":[537],"involved":[539],"designing":[541],"executing":[543],"experiments,":[544],"collecting":[545],"analyzing":[547],"data,":[548],"disseminating":[550],"findings":[552],"through":[553],"scholarly":[554],"publications.":[555],"dedication":[557],"demonstrates":[560],"its":[561],"commitment":[562],"scientific":[565,590],"understanding":[566],"promoting":[568],"technological":[569],"advancements.":[570],"Their":[571],"create":[577],"positive":[579],"society":[582],"contribute":[584],"overall":[587],"community.R":[591],"JosphineleelaR.":[592],"Josphineleela":[593],"her":[596,609],"Ph.D(Computer":[597],"Science":[598,631],"Engineering)":[599,615],"Sathyabama":[601],"2013.":[605],"completed":[608],"M.":[610],"E":[611],"(computer":[612],"sathyabama":[617],"more":[621,654],"than":[622,655],"20":[623],"years'":[624],"Computer":[630,690,717],"she":[633,721],"Information":[644],"Technology":[645],"Panimalar":[647],"Technology.":[650],"published":[653],"50":[656],"papers":[657],"national":[659],"level.":[662],"Image":[670],"processing,":[671],"Neural":[672],"Network,":[673],"Artificial":[674],"Intelligence,":[675],"Biomedical":[676],"Imaging":[677],"Soft":[679],"Computing":[680],"etc.":[681],"Distinguished":[686],"award":[688,698,715],"Society":[691,718],"Best":[696,706,713],"Project":[697],"Dr.Kalam":[700],"Educational":[701],"Trust":[702],"Tribal":[704],"Teacher":[707],"Award":[708],"IEAE.":[710],"got":[712],"Paper":[714],"Ind":[720],"\"Certificate":[724],"Appreciation\"":[726],"contributing":[728],"Proctor":[731],"\"IEEEXtreme":[733],"12.0\"":[734],"Programming.":[735],"\"In":[739],"appreciation":[740],"fostering":[742],"ecosystem":[744],"bridging":[745],"Government,":[746],"Industry":[747],"Academia":[749],"award\"":[750],"\"India":[752],"challenge":[754],"contest":[756],"2018":[757],"DST":[759],"&":[760],"Texas":[761],"Instrument\".":[762]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}