{"id":"https://openalex.org/W7130735600","doi":"https://doi.org/10.1109/ic2sdt68218.2025.11383756","title":"Comparative Analysis of Optimization Algorithms for Deep Learning-Based Medical Image Classification","display_name":"Comparative Analysis of Optimization Algorithms for Deep Learning-Based Medical Image Classification","publication_year":2025,"publication_date":"2025-12-04","ids":{"openalex":"https://openalex.org/W7130735600","doi":"https://doi.org/10.1109/ic2sdt68218.2025.11383756"},"language":"en","primary_location":{"id":"doi:10.1109/ic2sdt68218.2025.11383756","doi":"https://doi.org/10.1109/ic2sdt68218.2025.11383756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic2sdt68218.2025.11383756","pdf_url":null,"source":{"id":"https://openalex.org/S7407096262","display_name":"International Conference on Pioneering Developments in Computer Science & Digital Technologies (IC2SDT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Second International Conference on Pioneering Developments in Computer Science & Digital Technologies (IC2SDT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5126465417","display_name":"Diksha Pandey","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I44635919","display_name":"National Institute of Technology Delhi","ror":"https://ror.org/032twef21","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152752","https://openalex.org/I44635919"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Diksha Pandey","raw_affiliation_strings":["National Institute of Technology,Department of Applied Science,Delhi,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology,Department of Applied Science,Delhi,India","institution_ids":["https://openalex.org/I44635919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101570573","display_name":"Gautam Kumar","orcid":"https://orcid.org/0000-0003-4578-0082","observed_orcids":["https://orcid.org/0000-0003-4578-0082"]},"institutions":[{"id":"https://openalex.org/I44635919","display_name":"National Institute of Technology Delhi","ror":"https://ror.org/032twef21","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152752","https://openalex.org/I44635919"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gautam Kumar","raw_affiliation_strings":["National Institute of Technology,Department of Computer Science & Engineering,Delhi,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology,Department of Computer Science & Engineering,Delhi,India","institution_ids":["https://openalex.org/I44635919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I44635919"],"apc_list":null,"apc_paid":null,"fwci":0.368,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70778679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"503","last_page":"508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.5532000064849854,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.5532000064849854,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.2524000108242035,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.03350000083446503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/optimization-algorithms","display_name":"optimization algorithms","score":0.8899999856948853},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"gradient descent","score":0.44999998807907104},{"id":"https://openalex.org/keywords/adam-optimizer","display_name":"Adam optimizer","score":0.8970000147819519},{"id":"https://openalex.org/keywords/adadelta","display_name":"Adadelta","score":0.9490000009536743},{"id":"https://openalex.org/keywords/nadam","display_name":"Nadam","score":0.9409999847412109},{"id":"https://openalex.org/keywords/rmsprop","display_name":"RMSProp","score":0.9729999899864197},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"stochastic gradient descent","score":0.984000027179718},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9649999737739563},{"id":"https://openalex.org/keywords/medical-image-classification","display_name":"medical image classification","score":0.9700000286102295},{"id":"https://openalex.org/keywords/binary-classification","display_name":"binary classification","score":0.9639999866485596},{"id":"https://openalex.org/keywords/classification-accuracy","display_name":"classification accuracy","score":0.45500001311302185},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"confusion matrix","score":0.8920000195503235}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.694599986076355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6643000245094299},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5163000226020813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5115000009536743},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.4837000072002411},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4796000123023987},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.4620000123977661},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45489999651908875},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4129999876022339},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.39010000228881836},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.35899999737739563},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30550000071525574},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2621000111103058},{"id":"https://openalex.org/C92995354","wikidata":"https://www.wikidata.org/wiki/Q5165499","display_name":"Continuous optimization","level":4,"score":0.260699987411499},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic2sdt68218.2025.11383756","doi":"https://doi.org/10.1109/ic2sdt68218.2025.11383756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic2sdt68218.2025.11383756","pdf_url":null,"source":{"id":"https://openalex.org/S7407096262","display_name":"International Conference on Pioneering Developments in Computer Science & Digital Technologies (IC2SDT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Second International Conference on Pioneering Developments in Computer Science & Digital Technologies (IC2SDT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1995817737","https://openalex.org/W2143257933","https://openalex.org/W2765995311","https://openalex.org/W2782724031","https://openalex.org/W2902748903","https://openalex.org/W2912290085","https://openalex.org/W2971382582","https://openalex.org/W2995512232","https://openalex.org/W3036095178","https://openalex.org/W3084231313","https://openalex.org/W3088053597","https://openalex.org/W3152010813","https://openalex.org/W4225332951","https://openalex.org/W4281656136","https://openalex.org/W4283156191","https://openalex.org/W4283776244","https://openalex.org/W4289262214","https://openalex.org/W4292168379","https://openalex.org/W4309961895","https://openalex.org/W4310065372","https://openalex.org/W4383068182","https://openalex.org/W4385415770","https://openalex.org/W4386690781","https://openalex.org/W4387340756","https://openalex.org/W4390670395","https://openalex.org/W4402446139"],"related_works":["https://openalex.org/W7221446316","https://openalex.org/W7117961833","https://openalex.org/W2992251715","https://openalex.org/W4395669845","https://openalex.org/W4417515862","https://openalex.org/W4404577387","https://openalex.org/W4400579458","https://openalex.org/W7117450650","https://openalex.org/W4403126386","https://openalex.org/W4322625192"],"abstract_inverted_index":{"This":[0,112],"research":[1],"examines":[2],"and":[3,34,53,56,84,89,104,132],"compares":[4],"the":[5,17,27,41,44,64,68,81,91,94,98,118,127,130,133,136,142,145,150,163],"performance":[6,92,148],"of":[7,19,22,43,93,117,123,129,135,141,149,162],"six":[8,47],"distinct":[9],"optimization":[10,48,119,152,164],"methods":[11,49,95,120,153,165],"used":[12,62],"with":[13,67],"CNN":[14,70],"architecture":[15],"in":[16,40,96,121,147,168],"context":[18],"binary":[20],"classification":[21,78],"medical":[23,171],"images.":[24],"We":[25],"pre-processed":[26],"images":[28,99],"by":[29],"converting":[30],"them":[31],"to":[32,37,87,105,157,166],"grayscale":[33],"uniform":[35],"dimensions":[36],"ensure":[38],"uniformity":[39],"training":[42],"model.":[45],"The":[46,72,139],"(Adam,":[50],"Adadelta,":[51],"Nadam,":[52],"RMSprop,":[54],"FTRL,":[55],"Stochastic":[57],"Gradient":[58],"Descent":[59],"(SGD))":[60],"were":[61],"under":[63],"same":[65,69],"conditions":[66],"structure.":[71],"model":[73,131,137],"was":[74,110],"evaluated":[75],"based":[76],"on":[77,80,126],"accuracy":[79,134],"test":[82],"datasets":[83],"confusion":[85],"matrices":[86],"measure":[88],"analyze":[90],"classifying":[97],"into":[100],"their":[101,124],"respective":[102],"categories":[103],"which":[106,154],"class":[107],"each":[108],"image":[109],"assigned.":[111],"allowed":[113],"for":[114],"a":[115],"comparison":[116],"terms":[122],"influence":[125],"learning":[128,170],"prediction.":[138],"analysis":[140],"results":[143],"shows":[144],"difference":[146],"available":[151],"would":[155],"help":[156],"make":[158],"an":[159],"informed":[160],"choice":[161],"use":[167],"deep":[169],"imaging.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-02-21T00:00:00"}