{"id":"https://openalex.org/W3013783358","doi":"https://doi.org/10.1109/sbesc49506.2019.9046088","title":"Deep Learning applied to the Identification of Fruit Fly in Intelligent Traps","display_name":"Deep Learning applied to the Identification of Fruit Fly in Intelligent Traps","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3013783358","doi":"https://doi.org/10.1109/sbesc49506.2019.9046088","mag":"3013783358"},"language":"en","primary_location":{"id":"doi:10.1109/sbesc49506.2019.9046088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sbesc49506.2019.9046088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IX Brazilian Symposium on Computing Systems Engineering (SBESC)","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/A5056547836","display_name":"Valter A. M. Martins","orcid":"https://orcid.org/0000-0002-1384-9746"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Valter A. M. Martins","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil"],"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034037609","display_name":"Lucas Cordeiro Freitas","orcid":"https://orcid.org/0000-0002-3860-9327"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lucas C. Freitas","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil"],"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075071243","display_name":"Mar\u00edlton Sanchotene de Aguiar","orcid":"https://orcid.org/0000-0002-5247-6022"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marilton S. de Aguiar","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil"],"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085318038","display_name":"Lisane Brisolara","orcid":"https://orcid.org/0000-0003-3552-4456"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lisane B. de Brisolara","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil"],"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039538346","display_name":"Paulo R. Ferreira","orcid":"https://orcid.org/0000-0001-5631-6766"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Paulo R. Ferreira","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil"],"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056547836"],"corresponding_institution_ids":["https://openalex.org/I169248161"],"apc_list":null,"apc_paid":null,"fwci":1.2083,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.80339604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12043","display_name":"Insect behavior and control techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect 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"}},"topics":[{"id":"https://openalex.org/T12043","display_name":"Insect behavior and control techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect 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/T12894","display_name":"Date Palm Research Studies","score":0.9902999997138977,"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/T11706","display_name":"Forensic Entomology and Diptera Studies","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect 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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7042290568351746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6249403953552246},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5898836255073547},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5143314599990845},{"id":"https://openalex.org/keywords/ceratitis-capitata","display_name":"Ceratitis capitata","score":0.5085557699203491},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4694903492927551},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46457040309906006},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.46307456493377686},{"id":"https://openalex.org/keywords/trap","display_name":"Trap (plumbing)","score":0.4517698287963867},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44992128014564514},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44312429428100586},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.417126327753067},{"id":"https://openalex.org/keywords/tephritidae","display_name":"Tephritidae","score":0.40098023414611816},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.19262418150901794},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17569532990455627},{"id":"https://openalex.org/keywords/pest-analysis","display_name":"PEST analysis","score":0.17458319664001465},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.1598639190196991},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.09646362066268921}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7042290568351746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6249403953552246},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5898836255073547},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5143314599990845},{"id":"https://openalex.org/C2780492371","wikidata":"https://www.wikidata.org/wiki/Q250269","display_name":"Ceratitis capitata","level":4,"score":0.5085557699203491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4694903492927551},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46457040309906006},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.46307456493377686},{"id":"https://openalex.org/C121099081","wikidata":"https://www.wikidata.org/wiki/Q665580","display_name":"Trap (plumbing)","level":2,"score":0.4517698287963867},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44992128014564514},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44312429428100586},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.417126327753067},{"id":"https://openalex.org/C2776992364","wikidata":"https://www.wikidata.org/wiki/Q626843","display_name":"Tephritidae","level":3,"score":0.40098023414611816},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.19262418150901794},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17569532990455627},{"id":"https://openalex.org/C22508944","wikidata":"https://www.wikidata.org/wiki/Q568174","display_name":"PEST analysis","level":2,"score":0.17458319664001465},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.1598639190196991},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.09646362066268921},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sbesc49506.2019.9046088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sbesc49506.2019.9046088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IX Brazilian Symposium on Computing Systems Engineering (SBESC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.550000011920929,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W2004198234","https://openalex.org/W2008353316","https://openalex.org/W2034231583","https://openalex.org/W2040870580","https://openalex.org/W2047092277","https://openalex.org/W2057479043","https://openalex.org/W2098257359","https://openalex.org/W2101722791","https://openalex.org/W2117130368","https://openalex.org/W2147800946","https://openalex.org/W2148950015","https://openalex.org/W2156387975","https://openalex.org/W2161381512","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2285671993","https://openalex.org/W2325939864","https://openalex.org/W2549139847","https://openalex.org/W2775795276","https://openalex.org/W2810553234","https://openalex.org/W2903919202","https://openalex.org/W2949117887","https://openalex.org/W2963911037","https://openalex.org/W4233045210","https://openalex.org/W4247572081","https://openalex.org/W6638444622","https://openalex.org/W6638667902","https://openalex.org/W6682889407","https://openalex.org/W6684191040","https://openalex.org/W6700903540","https://openalex.org/W6747218270"],"related_works":["https://openalex.org/W2321696171","https://openalex.org/W3185071163","https://openalex.org/W582246981","https://openalex.org/W2033605469","https://openalex.org/W2763186540","https://openalex.org/W2788937376","https://openalex.org/W2946301105","https://openalex.org/W4252725919","https://openalex.org/W4249324233","https://openalex.org/W2614981891"],"abstract_inverted_index":{"This":[0,32],"paper":[1],"presents":[2],"a":[3,18,30,38,67,105,139,182,239,247],"novel":[4],"approach":[5,64],"to":[6,24,73,85,116,180,221,227],"the":[7,45,48,56,60,89,111,118,121,129,146,149,166,171,175,193,208,222,228],"identification":[8,33],"of":[9,12,17,20,47,59,107,141,148,210,230,249],"two":[10],"species":[11],"fruit":[13,150],"flies":[14,151],"as":[15],"part":[16],"network":[19],"intelligent":[21],"traps":[22],"designed":[23],"monitor":[25],"these":[26,87],"insects":[27,49],"population":[28],"in":[29,178],"plantation.":[31],"is":[34,163,203,218],"done":[35],"essentially":[36],"by":[37,136,188],"Convolutional":[39],"Neural":[40,83],"Network":[41,84],"(CNN)":[42],"which":[43,217],"learns":[44],"characteristics":[46],"based":[50],"on":[51,110,170],"their":[52,93],"images":[53,108],"made":[54],"from":[55],"adhesive":[57],"floor":[58],"trap.":[61],"The":[62,131],"proposed":[63],"also":[65],"uses":[66],"simple":[68],"Digital":[69],"Image":[70],"Processing":[71],"technique":[72],"detect":[74],"regions":[75],"that":[76,165,200],"are":[77,236],"likely":[78],"pests":[79],"and":[80,124,143,157,205,213],"an":[81,189],"Artificial":[82],"classify":[86],"into":[88],"right":[90],"class":[91],"given":[92],"characteristics.":[94],"We":[95,198],"have":[96,246],"trained":[97],"several":[98],"CNN":[99],"architectures,":[100],"with":[101,120,138,184],"different":[102],"configurations,":[103],"through":[104],"dataset":[106],"collected":[109],"field.":[112],"Our":[113],"aim":[114],"was":[115,134],"find":[117],"one":[119],"highest":[122],"precision":[123,140,202,248],"lower":[125],"time":[126,187],"needed":[127],"for":[128,145,207,238],"classification.":[130],"best":[132,194,223],"performance":[133,224],"achieved":[135],"ResNet18,":[137],"93.55%":[142],"91.28%":[144],"classification":[147,167,209],"focusing":[152],"here,":[153],"named":[154],"Ceratitis":[155,211],"capitata":[156,212],"Grapholita":[158,214],"molesta,":[159,215],"respectively.":[160],"As":[161],"it":[162],"required":[164],"occurs":[168],"embedded":[169],"trap,":[172],"we":[173,196],"exploit":[174],"SqueezeNet":[176],"architecture":[177],"order":[179],"achieve":[181],"model":[183,195],"less":[185],"inference":[186],"accuracy":[190],"trade-off":[191],"upon":[192],"assessed.":[197],"show":[199],"its":[201],"88.56%":[204],"90.60%,":[206],"respectively,":[216],"very":[219],"close":[220],"one.":[225],"According":[226],"expertise":[229],"our":[231,234],"partner":[232],"company,":[233],"results":[235],"worthwhile":[237],"real-world":[240],"application":[241],"since":[242],"general":[243],"human":[244],"laborers":[245],"about":[250],"85%.":[251]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}