{"id":"https://openalex.org/W4388951080","doi":"https://doi.org/10.1109/icccnt56998.2023.10306437","title":"Classification of Ocular Diseases using Retinal Fundus Images by Leveraging Advance Transfer Learning and Deep Learning Techniques","display_name":"Classification of Ocular Diseases using Retinal Fundus Images by Leveraging Advance Transfer Learning and Deep Learning Techniques","publication_year":2023,"publication_date":"2023-07-06","ids":{"openalex":"https://openalex.org/W4388951080","doi":"https://doi.org/10.1109/icccnt56998.2023.10306437"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt56998.2023.10306437","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10306437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5011505604","display_name":"Geethanjali Kher","orcid":null},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Geethanjali Kher","raw_affiliation_strings":["University of Delhi,Kirori Mal College,Department of Computer Science,Delhi,India","Department of Computer Science, Kirori Mal College, University of Delhi, Delhi, India"],"affiliations":[{"raw_affiliation_string":"University of Delhi,Kirori Mal College,Department of Computer Science,Delhi,India","institution_ids":["https://openalex.org/I110166357"]},{"raw_affiliation_string":"Department of Computer Science, Kirori Mal College, University of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033238131","display_name":"Vanshika Singh","orcid":"https://orcid.org/0000-0002-5762-8996"},"institutions":[{"id":"https://openalex.org/I162030827","display_name":"Thapar Institute of Engineering & Technology","ror":"https://ror.org/00wdq3744","country_code":"IN","type":"education","lineage":["https://openalex.org/I162030827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vanshika Singh","raw_affiliation_strings":["Thapar Institute of Engineering and Technology,Department of Electronic and Communication,Patiala,India","Department of Electronic and Communication, Thapar Institute of Engineering and Technology, Patiala, India"],"affiliations":[{"raw_affiliation_string":"Thapar Institute of Engineering and Technology,Department of Electronic and Communication,Patiala,India","institution_ids":["https://openalex.org/I162030827"]},{"raw_affiliation_string":"Department of Electronic and Communication, Thapar Institute of Engineering and Technology, Patiala, India","institution_ids":["https://openalex.org/I162030827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021573877","display_name":"Neelam Dabas","orcid":null},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Neelam Dabas","raw_affiliation_strings":["University of Delhi,Shyam Lal College,Department of Computer Science,Delhi,India","Department of Computer Science, Shyam Lal College, University of Delhi, Delhi, India"],"affiliations":[{"raw_affiliation_string":"University of Delhi,Shyam Lal College,Department of Computer Science,Delhi,India","institution_ids":["https://openalex.org/I110166357"]},{"raw_affiliation_string":"Department of Computer Science, Shyam Lal College, University of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108701146","display_name":"Rajni Bala","orcid":null},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajni Bala","raw_affiliation_strings":["University of Delhi,DDUC,Department of Computer Science,Delhi,India","Department of Computer Science, DDUC, University of Delhi, Delhi, India"],"affiliations":[{"raw_affiliation_string":"University of Delhi,DDUC,Department of Computer Science,Delhi,India","institution_ids":["https://openalex.org/I110166357"]},{"raw_affiliation_string":"Department of Computer Science, DDUC, University of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011505604"],"corresponding_institution_ids":["https://openalex.org/I110166357"],"apc_list":null,"apc_paid":null,"fwci":0.7088,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73299642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"24","issue":null,"first_page":"1","last_page":"5"},"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9950000047683716,"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/T12599","display_name":"Retinal and Optic Conditions","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.9028780460357666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7555360794067383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7269091606140137},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.7186537981033325},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6085976958274841},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5969265699386597},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.5457427501678467},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5390597581863403},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5287209153175354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47340378165245056},{"id":"https://openalex.org/keywords/glaucoma","display_name":"Glaucoma","score":0.4652944803237915},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.41488125920295715},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3927980363368988},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2938976287841797},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.2818463146686554},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.143740713596344},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.0965890884399414}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.9028780460357666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7555360794067383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7269091606140137},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.7186537981033325},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6085976958274841},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5969265699386597},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.5457427501678467},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5390597581863403},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5287209153175354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47340378165245056},{"id":"https://openalex.org/C2778527774","wikidata":"https://www.wikidata.org/wiki/Q159701","display_name":"Glaucoma","level":2,"score":0.4652944803237915},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.41488125920295715},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3927980363368988},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2938976287841797},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.2818463146686554},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.143740713596344},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.0965890884399414},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt56998.2023.10306437","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10306437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324131","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2006487828","https://openalex.org/W2107910786","https://openalex.org/W2169736040","https://openalex.org/W2194775991","https://openalex.org/W2234163201","https://openalex.org/W2620915497","https://openalex.org/W2806796234","https://openalex.org/W2946695482","https://openalex.org/W2963446712","https://openalex.org/W2966096374","https://openalex.org/W3081111549","https://openalex.org/W3098558149","https://openalex.org/W3101287485","https://openalex.org/W3143747286","https://openalex.org/W3159068660","https://openalex.org/W3203886254","https://openalex.org/W3204203484","https://openalex.org/W3205216105","https://openalex.org/W4206045132","https://openalex.org/W4225095641","https://openalex.org/W4292318628","https://openalex.org/W6637373629","https://openalex.org/W6762718338","https://openalex.org/W6907517211"],"related_works":["https://openalex.org/W1980571360","https://openalex.org/W4390929683","https://openalex.org/W3176448898","https://openalex.org/W4379115808","https://openalex.org/W3207986206","https://openalex.org/W2429379476","https://openalex.org/W1979866946","https://openalex.org/W4226141369","https://openalex.org/W3081392993","https://openalex.org/W2413307231"],"abstract_inverted_index":{"The":[0,67,97,130],"assistance":[1],"of":[2,11,18,71,113,132],"computer":[3],"aided":[4],"diagnostics":[5],"will":[6],"balance":[7],"the":[8,29,137],"insufficient":[9],"number":[10,17],"ophthalmologists":[12],"burdened":[13],"with":[14,118],"an":[15,79],"increasing":[16],"patients":[19],"suffering":[20],"from":[21],"Ocular":[22],"disease":[23,26],"(OD).":[24],"Multiple":[25],"prediction":[27],"offers":[28],"potential":[30],"to":[31,42,87,94],"address":[32],"this":[33],"problem.":[34],"Therefore,":[35],"we":[36],"propose":[37],"a":[38],"multi-class":[39],"classification":[40],"model":[41,69,115,135],"predict":[43],"Cataract":[44],"(C),":[45],"Glaucoma":[46],"(G)":[47],"and":[48,57,62,78,90,109,128],"Diabetic":[49],"Retinopathy":[50],"(DR)":[51],"using":[52,102],"Retinal":[53],"Fundus":[54],"Images":[55],"(RFI)":[56],"leveraging":[58],"Artificial":[59],"Intelligence":[60],"(AI)":[61],"Deep":[63],"Learning":[64],"(DL)":[65],"techniques.":[66],"proposed":[68,134],"consists":[70],"eight":[72],"convolution":[73],"layers,":[74,77],"five":[75],"max-pool":[76],"average-pool":[80],"layer.":[81],"LeakyReLu":[82],"activation":[83],"function":[84],"was":[85,100,116],"used":[86,93],"improve":[88],"results,":[89],"dropouts":[91],"were":[92],"regulate/handle":[95],"overfitting.":[96],"model\u2019s":[98],"performance":[99],"evaluated":[101],"Accuracy":[103],"(A),":[104],"Precision":[105],"(P),":[106],"Sensitivity":[107],"(S)":[108],"F1-score":[110],"(F1).":[111],"Comparison":[112],"our":[114,133],"done":[117],"state-of-the-art":[119],"pre-trained":[120,139],"network":[121],"models,":[122],"such":[123],"as":[124],"VGG16,":[125],"ResNet50,":[126],"EfficientNetB0,":[127],"DenseNet161.":[129],"results":[131],"outperforms":[136],"existing":[138],"models.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":3}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
