{"id":"https://openalex.org/W4400733367","doi":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","title":"Herbal plant leaves classification for traditional medicine using convolutional neural network","display_name":"Herbal plant leaves classification for traditional medicine using convolutional neural network","publication_year":2024,"publication_date":"2024-07-17","ids":{"openalex":"https://openalex.org/W4400733367","doi":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329"},"language":"en","primary_location":{"id":"doi:10.11591/ijai.v13.i3.pp3322-3329","doi":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","is_oa":true,"landing_page_url":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","pdf_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/24120/14141","source":{"id":"https://openalex.org/S2764408626","display_name":"IAES International Journal of Artificial Intelligence","issn_l":"2089-4872","issn":["2089-4872","2252-8938"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IAES International Journal of Artificial Intelligence (IJ-AI)","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/24120/14141","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050367670","display_name":"Alfharizky Fauzi","orcid":"https://orcid.org/0000-0002-3149-0044","observed_orcids":["https://orcid.org/0000-0002-3149-0044"]},"institutions":[{"id":"https://openalex.org/I4210087516","display_name":"Gunadarma University","ror":"https://ror.org/0028q1g19","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210087516"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Alfharizky Fauzi","raw_affiliation_strings":["Gunadarma University"],"raw_orcid":"https://orcid.org/0000-0002-3149-0044","affiliations":[{"raw_affiliation_string":"Gunadarma University","institution_ids":["https://openalex.org/I4210087516"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Busono Soerowirdjo","orcid":"https://orcid.org/0000-0002-4761-0012","observed_orcids":["https://orcid.org/0000-0002-4761-0012"]},"institutions":[{"id":"https://openalex.org/I4210087516","display_name":"Gunadarma University","ror":"https://ror.org/0028q1g19","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210087516"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Busono Soerowirdjo","raw_affiliation_strings":["Gunadarma University"],"raw_orcid":"https://orcid.org/0000-0002-4761-0012","affiliations":[{"raw_affiliation_string":"Gunadarma University","institution_ids":["https://openalex.org/I4210087516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073770677","display_name":"Emy Haryatmi","orcid":"https://orcid.org/0000-0003-1170-644X","observed_orcids":["https://orcid.org/0000-0003-1170-644X"]},"institutions":[{"id":"https://openalex.org/I4210087516","display_name":"Gunadarma University","ror":"https://ror.org/0028q1g19","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210087516"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Emy Haryatmi","raw_affiliation_strings":["Gunadarma University"],"raw_orcid":"https://orcid.org/0000-0003-1170-644X","affiliations":[{"raw_affiliation_string":"Gunadarma University","institution_ids":["https://openalex.org/I4210087516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210087516"],"apc_list":null,"apc_paid":null,"fwci":0.1406,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39340433,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":"3","first_page":"3322","last_page":"3322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5059000253677368,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5059000253677368,"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/T10616","display_name":"Smart Agriculture and AI","score":0.486299991607666,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/traditional-medicine","display_name":"traditional medicine","score":0.718999981880188},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9319999814033508},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.7689999938011169},{"id":"https://openalex.org/keywords/mobilenet","display_name":"MobileNet","score":0.9300000071525574},{"id":"https://openalex.org/keywords/lenet","display_name":"LeNet","score":0.9919999837875366},{"id":"https://openalex.org/keywords/leaf-image-recognition","display_name":"leaf image recognition","score":0.5730000138282776},{"id":"https://openalex.org/keywords/nicotiana-tabacum","display_name":"tobacco","score":0.9409999847412109}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7360298037528992},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6896084547042847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6054010987281799},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.5987629294395447},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5049050450325012},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.485895574092865},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4842481315135956},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4366668462753296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41513824462890625},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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":1,"locations":[{"id":"doi:10.11591/ijai.v13.i3.pp3322-3329","doi":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","is_oa":true,"landing_page_url":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","pdf_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/24120/14141","source":{"id":"https://openalex.org/S2764408626","display_name":"IAES International Journal of Artificial Intelligence","issn_l":"2089-4872","issn":["2089-4872","2252-8938"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IAES International Journal of Artificial Intelligence (IJ-AI)","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.11591/ijai.v13.i3.pp3322-3329","doi":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","is_oa":true,"landing_page_url":"https://doi.org/10.11591/ijai.v13.i3.pp3322-3329","pdf_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/24120/14141","source":{"id":"https://openalex.org/S2764408626","display_name":"IAES International Journal of Artificial Intelligence","issn_l":"2089-4872","issn":["2089-4872","2252-8938"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IAES International Journal of Artificial Intelligence (IJ-AI)","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400733367.pdf","grobid_xml":"https://content.openalex.org/works/W4400733367.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3018715636","https://openalex.org/W4319454898","https://openalex.org/W7222642684","https://openalex.org/W4416893712","https://openalex.org/W4412446331","https://openalex.org/W7125899718","https://openalex.org/W4387272162","https://openalex.org/W4417462244","https://openalex.org/W7143308636","https://openalex.org/W3095137335"],"abstract_inverted_index":{"The":[0,90,147,208],"classification":[1],"of":[2,45,75,92,130,156,190,215,226,238],"herbal":[3,98,157,191],"plant":[4,99,192],"leaves":[5,16,46,100,193],"can":[6],"be":[7],"implemented":[8],"in":[9,42,69,150,184],"agriculture":[10],"and":[11,55,104,125,145,163,173,194,206],"traditional":[12],"medicine.":[13],"Primarily,":[14],"sorting":[15,28,70],"was":[17,21,29,62,79,95,187,210],"done":[18,31],"before":[19],"it":[20,35,233],"processed":[22],"into":[23,196],"medicinal":[24,48],"ingredients.":[25,49],"Currently,":[26],"the":[27,43,73,106,119,213,218,229],"still":[30],"manually":[32],"by":[33,102],"writing":[34],"on":[36],"notes.":[37],"Sometimes":[38],"there":[39,78],"were":[40,153],"errors":[41],"selection":[44],"for":[47,217],"Herbal":[50],"plants":[51,158],"had":[52,177,222,234],"various":[53],"forms":[54],"are":[56],"very":[57],"greatly.":[58],"Artificial":[59],"intelligence":[60],"technology":[61],"needed":[63],"to":[64,96],"have":[65],"fast-paced":[66],"time":[67],"efficiency":[68],"leaves.":[71],"In":[72],"field":[74],"artificial":[76],"intelligence,":[77],"a":[80,143],"specific":[81],"or":[82,139],"detailed":[83],"learning":[84,112],"process":[85,232],"known":[86],"as":[87,123,135],"deep":[88,111],"learning.":[89],"objective":[91],"this":[93,151,185],"research":[94,152,186],"classify":[97],"images":[101,179,189],"applying":[103],"combining":[105],"convolutional":[107],"neural":[108],"network":[109],"(CNN)":[110],"method":[113],"with":[114,180,212],"data":[115,201,204,209,230],"augmentation":[116,231],"methods":[117],"without":[118],"pre-trained":[120],"architecture":[121],"such":[122,134],"MobileNet":[124],"LeNet.":[126],"This":[127],"technique":[128],"consisted":[129],"4":[131,154],"main":[132],"stages":[133],"collecting":[136],"data,":[137,141,198],"preprocessing":[138],"normalizing":[140],"building":[142],"model,":[144],"evaluating.":[146],"dataset":[148,182],"used":[149,183],"types":[155],"that":[159],"do":[160,164],"not":[161,165],"flower":[162],"bear":[166],"fruit":[167],"including":[168],"gulma":[169],"siam,":[170],"piduh,":[171],"sirih,":[172],"tobacco.":[174],"Each":[175],"class":[176],"250":[178],"total":[181],"1,000":[188],"divided":[195],"2":[197],"namely":[199],"80%":[200],"training":[202],"20%":[203],"testing,":[205],"validation.":[207],"trained":[211],"epoch":[214],"100":[216],"best":[219],"training.":[220],"It":[221],"an":[223,235],"accuracy":[224,236],"score":[225,237],"98.74%.":[227],"Without":[228],"91.43%.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2024-07-18T00:00:00"}