{"id":"https://openalex.org/W4312667011","doi":"https://doi.org/10.1109/ijcnn55064.2022.9891989","title":"Enhanced EfficientNet Network for Classifying Laparoscopy Videos using Transfer Learning Technique","display_name":"Enhanced EfficientNet Network for Classifying Laparoscopy Videos using Transfer Learning Technique","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312667011","doi":"https://doi.org/10.1109/ijcnn55064.2022.9891989"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9891989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9891989","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5057104617","display_name":"Divya Acharya","orcid":"https://orcid.org/0000-0003-0206-6428"},"institutions":[{"id":"https://openalex.org/I4210108074","display_name":"HCL Technologies (United States)","ror":"https://ror.org/0201da008","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108074","https://openalex.org/I96211989"]},{"id":"https://openalex.org/I96211989","display_name":"HCL Technologies (India)","ror":"https://ror.org/02nbb5780","country_code":"IN","type":"company","lineage":["https://openalex.org/I96211989"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Divya Acharya","raw_affiliation_strings":["HCL Technologies,India","HCL Technologies, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HCL Technologies,India","institution_ids":["https://openalex.org/I96211989","https://openalex.org/I4210108074"]},{"raw_affiliation_string":"HCL Technologies, India","institution_ids":["https://openalex.org/I96211989"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045900879","display_name":"Ramachandra Guda","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108074","display_name":"HCL Technologies (United States)","ror":"https://ror.org/0201da008","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108074","https://openalex.org/I96211989"]},{"id":"https://openalex.org/I96211989","display_name":"HCL Technologies (India)","ror":"https://ror.org/02nbb5780","country_code":"IN","type":"company","lineage":["https://openalex.org/I96211989"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Ramachandra Kaladhara Sarma Guda","raw_affiliation_strings":["HCL Technologies,India","HCL Technologies, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HCL Technologies,India","institution_ids":["https://openalex.org/I96211989","https://openalex.org/I4210108074"]},{"raw_affiliation_string":"HCL Technologies, India","institution_ids":["https://openalex.org/I96211989"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056550605","display_name":"Kameshwar Raovenkatajammalamadaka","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108074","display_name":"HCL Technologies (United States)","ror":"https://ror.org/0201da008","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108074","https://openalex.org/I96211989"]},{"id":"https://openalex.org/I96211989","display_name":"HCL Technologies (India)","ror":"https://ror.org/02nbb5780","country_code":"IN","type":"company","lineage":["https://openalex.org/I96211989"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Kameshwar Raovenkatajammalamadaka","raw_affiliation_strings":["HCL Technologies,India","HCL Technologies, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HCL Technologies,India","institution_ids":["https://openalex.org/I96211989","https://openalex.org/I4210108074"]},{"raw_affiliation_string":"HCL Technologies, India","institution_ids":["https://openalex.org/I96211989"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.915,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88780488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9954000115394592,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9954000115394592,"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/T10862","display_name":"AI in cancer detection","score":0.9908999800682068,"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/T10916","display_name":"Surgical Simulation and Training","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/computer-science","display_name":"Computer science","score":0.8053081035614014},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6731796860694885},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.641453742980957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5628873705863953},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4564646780490875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44588932394981384}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8053081035614014},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6731796860694885},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.641453742980957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5628873705863953},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4564646780490875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44588932394981384}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9891989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9891989","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":36,"referenced_works":["https://openalex.org/W1507561440","https://openalex.org/W1572533718","https://openalex.org/W2154801730","https://openalex.org/W2179331991","https://openalex.org/W2194775991","https://openalex.org/W2266464013","https://openalex.org/W2592929672","https://openalex.org/W2606308270","https://openalex.org/W2679674811","https://openalex.org/W2735666957","https://openalex.org/W2740610771","https://openalex.org/W2752481921","https://openalex.org/W2752782242","https://openalex.org/W2753115354","https://openalex.org/W2766183047","https://openalex.org/W2807103388","https://openalex.org/W2884771968","https://openalex.org/W2887873758","https://openalex.org/W2944008497","https://openalex.org/W2945372729","https://openalex.org/W2980225217","https://openalex.org/W2981919877","https://openalex.org/W2985778816","https://openalex.org/W2998595069","https://openalex.org/W3005485628","https://openalex.org/W3009323586","https://openalex.org/W3034526587","https://openalex.org/W3083641663","https://openalex.org/W3119332498","https://openalex.org/W3196495614","https://openalex.org/W3214142563","https://openalex.org/W4297775537","https://openalex.org/W6634160493","https://openalex.org/W6687400500","https://openalex.org/W6737664043","https://openalex.org/W6795911386"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557"],"abstract_inverted_index":{"Recent":[0],"days":[1],"have":[2,113],"seen":[3],"a":[4,18,52,199,227],"lot":[5],"of":[6,20,40,69,83,162,167,176,230],"interest":[7],"in":[8,43,97,246],"surgical":[9,41,206],"data":[10,134],"science":[11],"(SDS)":[12],"methods":[13],"and":[14,31,75,91,110,128,145,147,154,170,180,211,214],"imaging":[15],"technologies.":[16],"As":[17],"result":[19],"these":[21,186],"developments,":[22],"surgeons":[23],"may":[24],"execute":[25],"less":[26],"invasive":[27],"procedures.":[28],"Using":[29],"pathology":[30,33],"no":[32],"situations":[34],"to":[35,261],"classify":[36],"laparoscopic":[37],"video":[38,207],"pictures":[39],"activities,":[42],"this":[44],"research":[45],"work":[46],"authors":[47],"conducted":[48],"their":[49],"investigation":[50],"using":[51,101,118],"transfer":[53,120],"learning":[54,121,222],"technique":[55,122],"named":[56,73,201],"enhanced":[57,63,88,92,165],"ENet":[58],"(eENet)":[59],"network":[60,86],"based":[61],"on":[62],"EfficientNet":[64,71,85,168],"network.":[65],"Two":[66],"base":[67,174],"versions":[68,82],"the":[70,79,84,98,115,119,133,148,160,173,177,205,220,247,255,267],"model":[72,137,150,258],"ENetB0":[74],"ENetB7":[76],"along":[77],"with":[78,172,241],"two":[80],"proposed":[81,99,108,164,256],"as":[87,143,264,266],"EfficientNetB0":[89],"(eENetB0)":[90],"EfficientnetB7":[93],"(eENetB7)":[94],"are":[95],"implemented":[96],"framework":[100],"publicly":[102],"available":[103],"GLENDA":[104],"[1]":[105],"dataset.":[106],"The":[107],"eENetB0":[109,136],"eENetB7":[111,149,189],"models":[112,178,188],"classified":[114],"features":[116],"extracted":[117],"into":[123],"binary":[124],"classification.":[125],"For":[126,192,233],"70\u201330":[127],"10-fold":[129],"Cross-Validation":[130],"(10-fold":[131],"CV),":[132],"splitting":[135],"has":[138,151],"achieved":[139,152],"maximum":[140],"classification":[141],"accuracy":[142],"88.43%":[144],"97.59%,":[146],"97.72%":[153],"98.78%":[155],"accuracy.":[156],"We":[157,250],"also":[158,197],"compared":[159,237],"performance":[161,240],"our":[163,231,238],"version":[166,175],"(eENetB0":[169],"eENetB7)":[171],"(ENetB0":[179],"ENetB7)":[181],"it":[182],"shows":[183],"that":[184,203],"among":[185],"four":[187],"performed":[190],"well.":[191],"GUI-based":[193],"visualization":[194],"purposes,":[195],"we":[196,236],"created":[198],"platform":[200],"IAS.ai":[202,225],"detects":[204],"clips":[208],"having":[209],"blood":[210],"dry":[212],"scenarios":[213],"uses":[215],"explainable":[216],"AI":[217],"for":[218],"unboxing":[219],"deep":[221],"model's":[223],"performance.":[224],"is":[226],"real-time":[228],"application":[229],"approach.":[232],"further":[234],"validation,":[235],"framework's":[239],"other":[242],"leading":[243],"approaches":[244],"cited":[245],"literature":[248],"[2]\u2013[4].":[249],"can":[251],"see":[252],"how":[253],"well":[254,265],"eENet":[257],"does":[259],"compare":[260],"existing":[262],"models,":[263],"current":[268],"best":[269],"practices.":[270]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":7}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}
