{"id":"https://openalex.org/W7203667730","doi":"https://doi.org/10.1145/3805862.3805936","title":"A Late Fusion CNN Integrating RGB and Texture Features for Banana Ripeness Classification","display_name":"A Late Fusion CNN Integrating RGB and Texture Features for Banana Ripeness Classification","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7203667730","doi":"https://doi.org/10.1145/3805862.3805936"},"language":"en","primary_location":{"id":"doi:10.1145/3805862.3805936","doi":"https://doi.org/10.1145/3805862.3805936","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805862.3805936","pdf_url":null,"source":{"id":"https://openalex.org/S7407085933","display_name":"International Conference on Intelligent Information Technology (ICIIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 11th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3805862.3805936","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113199426","display_name":"Kheo Chau Mui","orcid":"https://orcid.org/0009-0007-0883-7242","observed_orcids":["https://orcid.org/0009-0007-0883-7242"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Kheo Chau Mui","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0007-0883-7242","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104295147","display_name":"Hoang-Tu Vo","orcid":"https://orcid.org/0009-0008-3879-6573","observed_orcids":["https://orcid.org/0009-0008-3879-6573"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hoang-Tu Vo","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0008-3879-6573","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147386900","display_name":"Thien Nguyen Thien","orcid":"https://orcid.org/0009-0005-1212-3547","observed_orcids":["https://orcid.org/0009-0005-1212-3547"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Thien Nguyen Thien","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0005-1212-3547","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102110585","display_name":"Phuc Pham Tien","orcid":"https://orcid.org/0009-0000-0310-6087","observed_orcids":["https://orcid.org/0009-0000-0310-6087"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Phuc Pham Tien","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0000-0310-6087","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101312635","display_name":"Huan Lam Le","orcid":"https://orcid.org/0009-0001-9989-2381","observed_orcids":["https://orcid.org/0009-0001-9989-2381"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huan Lam Le","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0001-9989-2381","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118965894","display_name":"Vuong Nguyen Phuc","orcid":"https://orcid.org/0009-0007-0101-3742","observed_orcids":["https://orcid.org/0009-0007-0101-3742"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Vuong Nguyen Phuc","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0007-0101-3742","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132752185","display_name":"Hieu Nguyen Trung","orcid":"https://orcid.org/0009-0004-4592-524X","observed_orcids":["https://orcid.org/0009-0004-4592-524X"]},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hieu Nguyen Trung","raw_affiliation_strings":["Information Technology Department, FPT University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0004-4592-524X","affiliations":[{"raw_affiliation_string":"Information Technology Department, FPT University, Cantho, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5147405199","display_name":"Phuong Lam Tan","orcid":"https://orcid.org/0009-0002-9805-659X","observed_orcids":["https://orcid.org/0009-0002-9805-659X"]},"institutions":[{"id":"https://openalex.org/I4405260942","display_name":"Tay Do University","ror":"https://ror.org/04gwjz789","country_code":"VN","type":"education","lineage":["https://openalex.org/I4405260942"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Phuong Lam Tan","raw_affiliation_strings":["Information Technology Department, Tay Do University, Cantho, Vietnam"],"raw_orcid":"https://orcid.org/0009-0002-9805-659X","affiliations":[{"raw_affiliation_string":"Information Technology Department, Tay Do University, Cantho, Vietnam","institution_ids":["https://openalex.org/I4405260942"]}]}],"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":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"485","last_page":"490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.7846999764442444,"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":0.7846999764442444,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1687999963760376,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.022099999710917473,"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/banana-ripeness-classification","display_name":"banana ripeness classification","score":0.9990000128746033},{"id":"https://openalex.org/keywords/decision-level-fusion","display_name":"decision fusion","score":0.7580000162124634},{"id":"https://openalex.org/keywords/texture-features","display_name":"texture features","score":0.6959999799728394},{"id":"https://openalex.org/keywords/resnet-50","display_name":"ResNet50","score":0.8109999895095825},{"id":"https://openalex.org/keywords/fruit-quality-evaluation","display_name":"fruit quality assessment","score":0.7829999923706055},{"id":"https://openalex.org/keywords/illumination-robustness","display_name":"illumination robustness","score":0.7200000286102295},{"id":"https://openalex.org/keywords/fruit-image-classification","display_name":"fruit image classification","score":0.3160000145435333}],"concepts":[{"id":"https://openalex.org/C2780393073","wikidata":"https://www.wikidata.org/wiki/Q7335586","display_name":"Ripeness","level":3,"score":0.8765000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8170999884605408},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7745000123977661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.708899974822998},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6868000030517578},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6100000143051147},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5511999726295471},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.527999997138977},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5120000243186951},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.3880999982357025},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.38690000772476196},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C84216515","wikidata":"https://www.wikidata.org/wiki/Q375677","display_name":"RGB color space","level":5,"score":0.29100000858306885},{"id":"https://openalex.org/C144743038","wikidata":"https://www.wikidata.org/wiki/Q3267765","display_name":"Texture filtering","level":5,"score":0.2743000090122223}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805862.3805936","doi":"https://doi.org/10.1145/3805862.3805936","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805862.3805936","pdf_url":null,"source":{"id":"https://openalex.org/S7407085933","display_name":"International Conference on Intelligent Information Technology (ICIIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 11th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805862.3805936","doi":"https://doi.org/10.1145/3805862.3805936","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805862.3805936","pdf_url":null,"source":{"id":"https://openalex.org/S7407085933","display_name":"International Conference on Intelligent Information Technology (ICIIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 11th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.5,"id":"https://metadata.un.org/sdg/2"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1836231398","https://openalex.org/W2044465660","https://openalex.org/W2063079640","https://openalex.org/W2117793557","https://openalex.org/W2143238858","https://openalex.org/W2163352848","https://openalex.org/W2566365295","https://openalex.org/W2790979755","https://openalex.org/W2895238724","https://openalex.org/W2962858109","https://openalex.org/W3173658886","https://openalex.org/W4295957164","https://openalex.org/W4313894588","https://openalex.org/W4323240860","https://openalex.org/W4378418349","https://openalex.org/W4392404277","https://openalex.org/W4403443297","https://openalex.org/W4404699089","https://openalex.org/W4411962160"],"related_works":["https://openalex.org/W7211960706","https://openalex.org/W4214583821","https://openalex.org/W4415883738","https://openalex.org/W7128426432","https://openalex.org/W4416556359","https://openalex.org/W4381300872","https://openalex.org/W6960819182","https://openalex.org/W4411562662","https://openalex.org/W7202408629","https://openalex.org/W7160513469"],"abstract_inverted_index":{"Banana":[0],"ripeness":[1,60,118],"classification":[2,154],"plays":[3],"an":[4,126],"important":[5],"role":[6],"in":[7],"automated":[8],"quality":[9],"assessment":[10],"and":[11,35,55,73,104,134,144,156,161],"supply":[12],"chain":[13],"management.":[14],"However,":[15],"most":[16],"existing":[17],"approaches":[18],"rely":[19],"solely":[20],"on":[21,85,115],"color":[22,74,143],"information":[23],"or":[24],"handcrafted":[25],"texture":[26,56,78,145,162],"descriptors,":[27],"which":[28],"are":[29,97],"often":[30],"sensitive":[31],"to":[32,70,88],"illumination":[33],"changes":[34],"surface":[36,91],"variations.":[37],"To":[38],"address":[39],"this":[40],"limitation,":[41],"we":[42],"propose":[43],"a":[44,66,81,116,148],"Late":[45],"Fusion":[46],"Convolutional":[47],"Neural":[48],"Network":[49],"(CNN)":[50],"that":[51,121,141],"integrates":[52],"complementary":[53],"RGB":[54,63],"features":[57],"for":[58,110],"robust":[59],"recognition.":[61],"The":[62,93],"stream":[64,79],"employs":[65],"pretrained":[67],"ResNet-50":[68],"backbone":[69],"capture":[71],"semantic":[72],"information,":[75],"while":[76],"the":[77,100,122],"is":[80],"lightweight":[82],"CNN":[83,136],"trained":[84],"grayscale":[86],"representations":[87],"extract":[89],"fine-grained":[90],"patterns.":[92],"two":[94],"feature":[95],"vectors":[96],"concatenated":[98],"at":[99],"late":[101],"fusion":[102,150],"stage":[103],"processed":[105],"by":[106],"fully":[107],"connected":[108],"layers":[109],"final":[111],"classification.":[112],"Experiments":[113],"conducted":[114],"banana":[117],"dataset":[119],"demonstrate":[120],"proposed":[123],"model":[124],"achieves":[125],"accuracy":[127,155],"of":[128],"98.22%,":[129],"outperforming":[130],"traditional":[131],"machine":[132],"learning":[133],"single-stream":[135],"models.":[137],"These":[138],"results":[139],"confirm":[140],"combining":[142],"cues":[146],"through":[147],"dual-stream":[149],"architecture":[151],"significantly":[152],"enhances":[153],"robustness":[157],"under":[158],"varying":[159],"lighting":[160],"conditions.":[163]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-19T00:00:00"}
