{"id":"https://openalex.org/W4316673363","doi":"https://doi.org/10.3390/rs15020538","title":"Deep Network Architectures as Feature Extractors for Multi-Label Classification of Remote Sensing Images","display_name":"Deep Network Architectures as Feature Extractors for Multi-Label Classification of Remote Sensing Images","publication_year":2023,"publication_date":"2023-01-16","ids":{"openalex":"https://openalex.org/W4316673363","doi":"https://doi.org/10.3390/rs15020538"},"language":"en","primary_location":{"id":"doi:10.3390/rs15020538","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15020538","pdf_url":"https://www.mdpi.com/2072-4292/15/2/538/pdf?version=1674198233","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/2/538/pdf?version=1674198233","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078991953","display_name":"Marjan Stoimchev","orcid":"https://orcid.org/0000-0003-4444-3877"},"institutions":[{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]},{"id":"https://openalex.org/I4210113529","display_name":"Jo\u017eef Stefan International Postgraduate School","ror":"https://ror.org/01hdkb925","country_code":"SI","type":"education","lineage":["https://openalex.org/I4210113529"]}],"countries":["SI"],"is_corresponding":true,"raw_author_name":"Marjan Stoimchev","raw_affiliation_strings":["Department of Knowledge Technologies, Jo\u017eef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia","Jo\u017eef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia"],"raw_orcid":"https://orcid.org/0000-0003-4444-3877","affiliations":[{"raw_affiliation_string":"Department of Knowledge Technologies, Jo\u017eef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia","institution_ids":["https://openalex.org/I3006985408"]},{"raw_affiliation_string":"Jo\u017eef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210113529"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004076545","display_name":"Dragi Kocev","orcid":"https://orcid.org/0000-0003-0687-0878"},"institutions":[{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]},{"id":"https://openalex.org/I4210113529","display_name":"Jo\u017eef Stefan International Postgraduate School","ror":"https://ror.org/01hdkb925","country_code":"SI","type":"education","lineage":["https://openalex.org/I4210113529"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Dragi Kocev","raw_affiliation_strings":["Bias Variance Labs, 1000 Ljubljana, Slovenia","Department of Knowledge Technologies, Jo\u017eef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia","Jo\u017eef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia"],"raw_orcid":"https://orcid.org/0000-0003-0687-0878","affiliations":[{"raw_affiliation_string":"Bias Variance Labs, 1000 Ljubljana, Slovenia","institution_ids":[]},{"raw_affiliation_string":"Department of Knowledge Technologies, Jo\u017eef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia","institution_ids":["https://openalex.org/I3006985408"]},{"raw_affiliation_string":"Jo\u017eef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210113529"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064609702","display_name":"Sa\u0161o D\u017eeroski","orcid":"https://orcid.org/0000-0003-2363-712X"},"institutions":[{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]},{"id":"https://openalex.org/I4210113529","display_name":"Jo\u017eef Stefan International Postgraduate School","ror":"https://ror.org/01hdkb925","country_code":"SI","type":"education","lineage":["https://openalex.org/I4210113529"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Sa\u0161o D\u017eeroski","raw_affiliation_strings":["Department of Knowledge Technologies, Jo\u017eef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia","Jo\u017eef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia"],"raw_orcid":"https://orcid.org/0000-0003-2363-712X","affiliations":[{"raw_affiliation_string":"Department of Knowledge Technologies, Jo\u017eef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia","institution_ids":["https://openalex.org/I3006985408"]},{"raw_affiliation_string":"Jo\u017eef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210113529"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5078991953"],"corresponding_institution_ids":["https://openalex.org/I3006985408","https://openalex.org/I4210113529"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":2.5891,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.90267159,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"15","issue":"2","first_page":"538","last_page":"538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9902999997138977,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9855999946594238,"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/computer-science","display_name":"Computer science","score":0.8552975654602051},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6686649322509766},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6583471298217773},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5666113495826721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5498960018157959},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5483123660087585},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5345852375030518},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5320699214935303},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5316624641418457},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4869290590286255},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47973576188087463},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4457279145717621},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41241759061813354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3827277421951294}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8552975654602051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6686649322509766},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6583471298217773},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5666113495826721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5498960018157959},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5483123660087585},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5345852375030518},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5320699214935303},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5316624641418457},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4869290590286255},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47973576188087463},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4457279145717621},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41241759061813354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3827277421951294},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15020538","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15020538","pdf_url":"https://www.mdpi.com/2072-4292/15/2/538/pdf?version=1674198233","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6374a14d07514e8281727904c1e2ffcf","is_oa":true,"landing_page_url":"https://doaj.org/article/6374a14d07514e8281727904c1e2ffcf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 2, p 538 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/2/538/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15020538","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 2; Pages: 538","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15020538","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15020538","pdf_url":"https://www.mdpi.com/2072-4292/15/2/538/pdf?version=1674198233","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G7530123626","display_name":"Knowledge Technologies","funder_award_id":"P2-0103","funder_id":"https://openalex.org/F4320322554","funder_display_name":"Javna Agencija za Raziskovalno Dejavnost RS"},{"id":"https://openalex.org/G8552916670","display_name":"Predictive clustering on data streams","funder_award_id":"J2-2505","funder_id":"https://openalex.org/F4320322554","funder_display_name":"Javna Agencija za Raziskovalno Dejavnost RS"}],"funders":[{"id":"https://openalex.org/F4320322554","display_name":"Javna Agencija za Raziskovalno Dejavnost RS","ror":"https://ror.org/059bp8k51"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4316673363.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W1686810756","https://openalex.org/W1980038761","https://openalex.org/W2009985472","https://openalex.org/W2101234009","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2515866431","https://openalex.org/W2766407278","https://openalex.org/W2766938848","https://openalex.org/W2809537360","https://openalex.org/W2884821995","https://openalex.org/W2889985731","https://openalex.org/W2932399282","https://openalex.org/W2946948417","https://openalex.org/W2958781163","https://openalex.org/W2963745697","https://openalex.org/W2986943971","https://openalex.org/W2996836954","https://openalex.org/W3011869042","https://openalex.org/W3027532550","https://openalex.org/W3054552769","https://openalex.org/W3089682028","https://openalex.org/W3091842132","https://openalex.org/W3099319035","https://openalex.org/W3099352527","https://openalex.org/W3102112912","https://openalex.org/W3105577662","https://openalex.org/W3111813289","https://openalex.org/W3165630282","https://openalex.org/W3165730205","https://openalex.org/W3186032668","https://openalex.org/W3194498659","https://openalex.org/W3196522548","https://openalex.org/W3208011655","https://openalex.org/W3208530345","https://openalex.org/W3216149117","https://openalex.org/W4224245290","https://openalex.org/W4313419997","https://openalex.org/W4318833168","https://openalex.org/W6675354045","https://openalex.org/W6770231179","https://openalex.org/W6799693294"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3183901164","https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3176438653"],"abstract_inverted_index":{"Data":[0],"in":[1,15,24,233,239,300,351],"the":[2,40,53,92,164,169,184,210,252,260,263,323,339,352],"form":[3],"of":[4,34,47,68,86,120,166,187,219,243,288,302,358],"images":[5,20,80],"are":[6,183,231,266,311],"now":[7,22],"generated":[8],"at":[9],"an":[10,101,234,284],"unprecedented":[11],"rate.":[12],"A":[13],"case":[14,54],"point":[16],"is":[17,58,94,113,122,327,338],"remote":[18,41],"sensing":[19,42],"(RSI),":[21],"available":[23,293],"large-scale":[25],"RSI":[26,121,294],"archives,":[27],"which":[28,137,337],"have":[29,75,159,178],"attracted":[30],"a":[31,64,155,179,347,355],"considerable":[32],"amount":[33],"research":[35],"on":[36,104,209],"image":[37,50,57,73],"classification":[38,51,116,119,153],"within":[39],"community.":[43],"The":[44,108,118,229,317],"basic":[45],"task":[46,165],"single-target":[48,152],"multi-class":[49],"considers":[52],"where":[55,214],"each":[56],"assigned":[59],"exactly":[60],"one":[61],"label":[62],"from":[63],"predefined":[65,192],"finite":[66],"set":[67],"class":[69,186],"labels.":[70],"Recently,":[71],"however,":[72],"annotations":[74],"become":[76],"increasingly":[77],"complex,":[78],"with":[79,82,268,354],"labeled":[81],"several":[83,291],"labels":[84],"(instead":[85],"just":[87],"one).":[88],"In":[89,198,259],"other":[90,170],"words,":[91],"goal":[93],"to":[95,100,195,329,371],"assign":[96],"multiple":[97],"semantic":[98],"categories":[99],"image,":[102],"based":[103,208],"its":[105],"high-level":[106],"context.":[107],"corresponding":[109],"machine":[110],"learning":[111,212],"tasks":[112],"called":[114],"multi-label":[115],"(MLC).":[117],"currently":[123],"predominantly":[124],"addressed":[125],"by":[126],"deep":[127,373],"neural":[128,134],"network":[129,332],"(DNN)":[130],"approaches,":[131],"especially":[132,314],"convolutional":[133],"networks":[135],"(CNNs),":[136],"can":[138,366],"be":[139],"utilized":[140],"as":[141,144,146,224,246,256,275,335,344,346],"feature":[142,193,257,348],"extractors":[143],"well":[145,345],"end-to-end":[147,235,342,372],"methods.":[148],"After":[149],"only":[150],"considering":[151],"for":[154,176,205,272,321,364],"long":[156,180],"period,":[157],"DNNs":[158],"recently":[160],"emerged":[161],"that":[162,249],"address":[163],"MLC.":[167],"On":[168],"hand,":[171],"trees":[172],"and":[173,182,227,237,255,278,296],"tree":[174,269,362],"ensembles":[175,363],"MLC":[177,188,253,304,365],"tradition":[181],"best-performing":[185],"methods,":[189],"but":[190],"need":[191],"representations":[194,265],"operate":[196],"on.":[197],"this":[199],"work,":[200],"we":[201,215],"explore":[202],"different":[203,217,241],"strategies":[204],"model":[206],"training":[207],"transfer":[211],"paradigm,":[213],"utilize":[216],"families":[218],"(pre-trained)":[220],"CNN":[221],"architectures,":[222,333],"such":[223,274,334],"VGG,":[225],"EfficientNet,":[226],"ResNet.":[228],"architectures":[230],"trained":[232],"manner":[236],"used":[238,267],"two":[240],"modes":[242],"operation,":[244],"namely,":[245],"standalone":[247],"models":[248],"directly":[250],"perform":[251],"task,":[254,325],"extractors.":[258],"latter":[261],"case,":[262],"learned":[264],"ensemble":[270],"methods":[271,289],"MLC,":[273],"random":[276],"forests":[277],"extremely":[279],"randomized":[280],"trees.":[281],"We":[282],"conduct":[283],"extensive":[285],"experimental":[286],"analysis":[287],"over":[290],"publicly":[292],"datasets":[295,353],"evaluate":[297],"their":[298],"effectiveness":[299],"terms":[301],"standard":[303],"measures.":[305],"Of":[306],"these,":[307],"ranking-based":[308],"evaluation":[309],"measures":[310],"most":[312],"relevant,":[313],"ranking":[315],"loss.":[316],"results":[318],"show":[319],"that,":[320],"addressing":[322],"RSI-MLC":[324],"it":[326],"favorable":[328],"use":[330],"lightweight":[331],"EfficientNet-B2,":[336],"best":[340],"performing":[341],"approach,":[343],"extractor.":[349],"Furthermore,":[350],"limited":[356],"number":[357],"images,":[359],"using":[360],"traditional":[361],"yield":[367],"better":[368],"performance":[369],"compared":[370],"approaches.":[374]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":7}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
