{"id":"https://openalex.org/W4405180335","doi":"https://doi.org/10.1109/ict4da62874.2024.10777203","title":"An Ensemble Feature Extraction Approach for Ethiopian Coffee Beans Variant Identification","display_name":"An Ensemble Feature Extraction Approach for Ethiopian Coffee Beans Variant Identification","publication_year":2024,"publication_date":"2024-11-18","ids":{"openalex":"https://openalex.org/W4405180335","doi":"https://doi.org/10.1109/ict4da62874.2024.10777203"},"language":"en","primary_location":{"id":"doi:10.1109/ict4da62874.2024.10777203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ict4da62874.2024.10777203","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)","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":null,"display_name":"Wakjira Tesfaye","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122757","display_name":"Asossa University","ror":"https://ror.org/02nkn4852","country_code":"ET","type":"education","lineage":["https://openalex.org/I4210122757"]}],"countries":["ET"],"is_corresponding":false,"raw_author_name":"Wakjira Tesfaye","raw_affiliation_strings":["Assosa University,Electrical and Computer Engineering,Assosa,Ethiopia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Assosa University,Electrical and Computer Engineering,Assosa,Ethiopia","institution_ids":["https://openalex.org/I4210122757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115062176","display_name":"Tenagne Fikirie","orcid":null},"institutions":[{"id":"https://openalex.org/I57092466","display_name":"Bahir Dar University","ror":"https://ror.org/01670bg46","country_code":"ET","type":"education","lineage":["https://openalex.org/I57092466"]}],"countries":["ET"],"is_corresponding":false,"raw_author_name":"Tenagne Fikirie","raw_affiliation_strings":["Bahir Dar University,Faculty of Electrical and Computer Engineering, Bahir Dar Institute of Technology,Bahir Dar,Ethiopia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bahir Dar University,Faculty of Electrical and Computer Engineering, Bahir Dar Institute of Technology,Bahir Dar,Ethiopia","institution_ids":["https://openalex.org/I57092466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20069771,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T10616","display_name":"Smart Agriculture and AI","score":0.9818999767303467,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6680424213409424},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5888205766677856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5672585368156433},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5341576337814331},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4992561340332031},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.47020870447158813},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.09272420406341553},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09269186854362488},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.08932146430015564},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.06800004839897156}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6680424213409424},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5888205766677856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5672585368156433},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5341576337814331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4992561340332031},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.47020870447158813},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.09272420406341553},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09269186854362488},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.08932146430015564},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06800004839897156}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ict4da62874.2024.10777203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ict4da62874.2024.10777203","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2062577170","https://openalex.org/W2090922444","https://openalex.org/W2227159265","https://openalex.org/W2333057761","https://openalex.org/W2518241345","https://openalex.org/W2622826443","https://openalex.org/W2783391412","https://openalex.org/W2907920216","https://openalex.org/W3017097154","https://openalex.org/W3045034870","https://openalex.org/W3049534004","https://openalex.org/W3095448153","https://openalex.org/W3198136258","https://openalex.org/W4206329475","https://openalex.org/W4206832422","https://openalex.org/W4238173028","https://openalex.org/W4249745911","https://openalex.org/W4293278234","https://openalex.org/W4318042239","https://openalex.org/W6688978380"],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640","https://openalex.org/W2049538278"],"abstract_inverted_index":{"Ethiopia\u2019s":[0],"primary":[1],"export":[2],"is":[3,59,66,77],"coffee,":[4],"which":[5,58,142],"contributes":[6],"significantly":[7],"to":[8,64,68,78,90,123,162,175],"the":[9,91,149,164,209,225],"country\u2019s":[10],"foreign":[11],"exchange":[12],"earnings.":[13],"In":[14],"Ethiopia,":[15],"there":[16],"are":[17,47],"numerous":[18],"types":[19],"of":[20,37,74,137,148],"coffee":[21,45,70,87,145,177,206],"beans.":[22,71,146],"Based":[23],"on":[24,50,224],"their":[25],"respective":[26],"geographic":[27],"origins,":[28],"these":[29],"beans":[30,46,178],"differ":[31],"from":[32,131,204],"one":[33],"another":[34],"in":[35],"terms":[36],"quality,":[38],"color,":[39],"shape,":[40],"and":[41,62,108,114,158,169,197,215],"other":[42],"characteristics.":[43],"These":[44],"categorized":[48],"based":[49],"where":[51,93],"they":[52,94,181],"were":[53,95,129,154,173,182],"grown.":[54,96],"However,":[55],"visual":[56],"inspection,":[57],"subjective,":[60],"time-consuming,":[61],"prone":[63],"error,":[65],"used":[67,122,155,174],"categorize":[69],"The":[72,134,228],"goal":[73],"this":[75],"research":[76,186],"create":[79],"a":[80],"suitable":[81],"system":[82],"that":[83,232],"categorizes":[84],"various":[85],"Ethiopian":[86],"varietals":[88],"according":[89],"location":[92],"Six":[97],"coffee-growing":[98],"regions":[99],"provided":[100],"sample":[101],"coffees":[102],"(Harar,":[103],"Jimma,":[104],"Limu,":[105],"Sidama,":[106],"Yirgachafe,":[107],"Wombera).":[109],"To":[110],"reduce":[111],"environmental":[112],"influences":[113],"eliminate":[115],"variance,":[116],"an":[117],"Epson":[118],"L360":[119],"scanner":[120],"was":[121,140],"capture":[124],"input":[125],"images.":[126],"100":[127],"images":[128,138],"taken":[130,139],"each":[132,205],"region.":[133],"total":[135,150],"number":[136],"600,":[141],"contained":[143],"12604":[144],"Out":[147],"data":[151],"sets,":[152],"75%":[153],"for":[156,160,208],"training":[157],"25%":[159],"testing":[161],"assess":[163],"classification":[165,210,237],"accuracy.":[166,238],"Morphological":[167],"operations":[168],"marker-based":[170],"watershed":[171],"algorithms":[172],"segment":[176],"even":[179],"if":[180],"mutually":[183],"touched.":[184],"This":[185],"extracted":[187,226],"sixty-four":[188],"Convolutional":[189],"neural":[190],"network":[191],"(CNN)":[192],"features,":[193],"five":[194,198],"morphological":[195],"features":[196,203],"Gray-Level":[199],"Co-occurrence":[200],"Matrix":[201],"(GLCM)":[202],"bean":[207],"process.":[211],"K-nearest":[212],"neighbor":[213],"(KNN)":[214],"Support":[216],"Vector":[217],"Machine":[218],"(SVM)":[219],"classifiers":[220],"have":[221],"been":[222],"evaluated":[223],"feature.":[227],"experimental":[229],"result":[230],"showed":[231],"SVM":[233],"gave":[234],"(90.16%)":[235],"better":[236]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}