{"id":"https://openalex.org/W3028375955","doi":"https://doi.org/10.1109/cis-ram47153.2019.9095778","title":"Tomato Fruit Image Dataset for Deep Transfer Learning-based Defect Detection","display_name":"Tomato Fruit Image Dataset for Deep Transfer Learning-based Defect Detection","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3028375955","doi":"https://doi.org/10.1109/cis-ram47153.2019.9095778","mag":"3028375955"},"language":"en","primary_location":{"id":"doi:10.1109/cis-ram47153.2019.9095778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cis-ram47153.2019.9095778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5033803843","display_name":"Robert G. de Luna","orcid":"https://orcid.org/0009-0007-8633-9724"},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Robert G. de Luna","raw_affiliation_strings":["Gokongwei College of Engineering, De La Salle University Manila, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gokongwei College of Engineering, De La Salle University Manila, Philippines","institution_ids":["https://openalex.org/I5996616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027440897","display_name":"Elmer P. Dadios","orcid":"https://orcid.org/0000-0002-5751-389X"},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Elmer P. Dadios","raw_affiliation_strings":["Gokongwei College of Engineering, De La Salle University Manila, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gokongwei College of Engineering, De La Salle University Manila, Philippines","institution_ids":["https://openalex.org/I5996616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084335648","display_name":"Argel A. Bandala","orcid":"https://orcid.org/0000-0002-3568-4858"},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Argel A. Bandala","raw_affiliation_strings":["Gokongwei College of Engineering, De La Salle University Manila, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gokongwei College of Engineering, De La Salle University Manila, Philippines","institution_ids":["https://openalex.org/I5996616"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043106023","display_name":"Ryan Rhay P. Vicerra","orcid":"https://orcid.org/0000-0002-8824-3749"},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Ryan Rhay P. Vicerra","raw_affiliation_strings":["Gokongwei College of Engineering, De La Salle University Manila, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gokongwei College of Engineering, De La Salle University Manila, Philippines","institution_ids":["https://openalex.org/I5996616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5996616"],"apc_list":null,"apc_paid":null,"fwci":5.7378,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.96408318,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"356","last_page":"361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9991999864578247,"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":0.9818999767303467,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9233999848365784,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.7735291123390198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7664249539375305},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7003617286682129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6353625059127808},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6182043552398682},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.6035982370376587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5186206698417664},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4502406418323517},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4143914580345154},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3859768509864807},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33251190185546875},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08268368244171143}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7735291123390198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7664249539375305},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7003617286682129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6353625059127808},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6182043552398682},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.6035982370376587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5186206698417664},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4502406418323517},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4143914580345154},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3859768509864807},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33251190185546875},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08268368244171143},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cis-ram47153.2019.9095778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cis-ram47153.2019.9095778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2047653713","https://openalex.org/W2304821224","https://openalex.org/W2542943690","https://openalex.org/W2557371538","https://openalex.org/W2587331008","https://openalex.org/W2609151886","https://openalex.org/W2737534312","https://openalex.org/W2756694293","https://openalex.org/W2758893285","https://openalex.org/W2785381287","https://openalex.org/W2787219651","https://openalex.org/W2809272686","https://openalex.org/W2891251953","https://openalex.org/W2894058049","https://openalex.org/W2901609506","https://openalex.org/W2920740547","https://openalex.org/W2941816431","https://openalex.org/W2947597709","https://openalex.org/W2951631494","https://openalex.org/W2952110468","https://openalex.org/W2955075236","https://openalex.org/W2962782553"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W3192840557","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W4375928479","https://openalex.org/W3131673289","https://openalex.org/W3178390372","https://openalex.org/W3198847674"],"abstract_inverted_index":{"Tomato":[0],"is":[1,38,47,201],"considered":[2],"as":[3,115,156,172],"one":[4],"of":[5,16,67,72,74,81,90,110,139,164,213,215],"the":[6,13,17,25,39,79,124,134,140,162,165,188,194,202,211,218,223],"vegetable":[7],"crops":[8],"with":[9,119],"highest":[10],"demand":[11],"in":[12,44,210,217],"Philippines.":[14],"Job":[15],"farmers":[18],"does":[19],"not":[20],"end":[21],"after":[22],"harvesting":[23],"since":[24],"harvested":[26],"tomatoes":[27],"needed":[28],"to":[29,33,57,159,207],"be":[30,208],"sorted":[31],"according":[32],"its":[34],"size.":[35],"Manual":[36],"sorting":[37,45,66],"most":[40],"widely":[41],"recognized":[42],"strategy":[43],"but":[46],"very":[48,55],"dependent":[49],"on":[50],"human":[51],"interpretation":[52],"and":[53,105,118,137,148,170,191],"thus,":[54],"prone":[56],"error.":[58],"This":[59],"research":[60],"proposed":[61],"a":[62,85,94],"solution":[63],"that":[64,178,199],"provides":[65],"tomato":[68,96,112,219],"fruit":[69,97,220],"by":[70],"detection":[71,89,212],"presence":[73,214],"defect.":[75],"The":[76],"study":[77],"presented":[78],"generation":[80],"image":[82,126],"dataset":[83,224],"for":[84,133,187,193],"deep":[86,142,204],"learning":[87,143,205],"approach":[88],"defects":[91],"based":[92,221],"from":[93,222],"single":[95],"image.":[98],"Models":[99],"were":[100],"implemented":[101],"using":[102,123,168],"OpenCV":[103],"libraries":[104],"Python":[106],"programming.":[107],"A":[108],"total":[109],"1200":[111],"images":[113,130,153,158],"classified":[114],"no":[116],"defect":[117,120,216],"are":[121,131,154],"gathered":[122],"improvised":[125],"capturing":[127],"box.":[128],"These":[129],"used":[132,155,209],"training,":[135],"validation,":[136],"testing":[138,157],"three":[141],"models":[144,167],"namely;":[145],"VGG16,":[146],"InceptionV3,":[147],"ResNet50.":[149,195],"From":[150],"this,":[151],"240":[152],"assess":[160],"independently":[161],"performance":[163,173],"trained":[166],"accuracy":[169,183],"F1-score":[171],"metrics.":[174],"Experiment":[175],"results":[176],"shown":[177],"VGG16":[179,200],"has":[180],"95.75-95.92-98.75":[181],"training-validation-testing":[182],"percentage":[184],"performance,":[185],"56.38-59.24-58.33":[186],"InceptionV3":[189],"model,":[190],"90.58-58.46-64.58":[192],"Comparative":[196],"analysis":[197],"revealed":[198],"best":[203],"model":[206],"gathered.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
