{"id":"https://openalex.org/W4382725322","doi":"https://doi.org/10.1007/s10489-023-04799-8","title":"Fruit ripeness identification using transformers","display_name":"Fruit ripeness identification using transformers","publication_year":2023,"publication_date":"2023-06-29","ids":{"openalex":"https://openalex.org/W4382725322","doi":"https://doi.org/10.1007/s10489-023-04799-8"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-023-04799-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04799-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04799-8.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04799-8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039140889","display_name":"Bingjie Xiao","orcid":"https://orcid.org/0000-0002-8791-1821"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Bingjie Xiao","raw_affiliation_strings":["Auckland University of Technology, Auckland, 1010, New Zealand"],"affiliations":[{"raw_affiliation_string":"Auckland University of Technology, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I39854758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042399868","display_name":"Minh Nguyen","orcid":"https://orcid.org/0000-0002-2757-8350"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Minh Nguyen","raw_affiliation_strings":["Auckland University of Technology, Auckland, 1010, New Zealand"],"affiliations":[{"raw_affiliation_string":"Auckland University of Technology, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I39854758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064286235","display_name":"Wei Qi Yan","orcid":"https://orcid.org/0009-0006-5891-9919"},"institutions":[{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Wei Qi Yan","raw_affiliation_strings":["Auckland University of Technology, Auckland, 1010, New Zealand"],"affiliations":[{"raw_affiliation_string":"Auckland University of Technology, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I39854758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039140889"],"corresponding_institution_ids":["https://openalex.org/I39854758"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":15.0732,"has_fulltext":true,"cited_by_count":38,"citation_normalized_percentile":{"value":0.98912938,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"53","issue":"19","first_page":"22488","last_page":"22499"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9988999962806702,"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":0.9988999962806702,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9961000084877014,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9732000231742859,"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/computer-science","display_name":"Computer science","score":0.8215864300727844},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7381082773208618},{"id":"https://openalex.org/keywords/ripeness","display_name":"Ripeness","score":0.5642842054367065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5577911734580994},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.498089075088501},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4612933397293091},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43321019411087036},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4293003976345062},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3281683325767517},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.13591799139976501},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08765295147895813},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07389557361602783}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8215864300727844},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7381082773208618},{"id":"https://openalex.org/C2780393073","wikidata":"https://www.wikidata.org/wiki/Q7335586","display_name":"Ripeness","level":3,"score":0.5642842054367065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5577911734580994},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.498089075088501},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4612933397293091},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43321019411087036},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4293003976345062},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3281683325767517},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.13591799139976501},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08765295147895813},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07389557361602783},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.0},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C172353545","wikidata":"https://www.wikidata.org/wiki/Q2121926","display_name":"Ripening","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10489-023-04799-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04799-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04799-8.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:openrepository.aut.ac.nz:10292/16551","is_oa":true,"landing_page_url":"http://hdl.handle.net/10292/16551","pdf_url":null,"source":{"id":"https://openalex.org/S4306401809","display_name":"Tuwhera (Auckland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39854758","host_organization_name":"Auckland University of Technology","host_organization_lineage":["https://openalex.org/I39854758"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1007/s10489-023-04799-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04799-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04799-8.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310339","display_name":"Auckland University of Technology, New Zealand","ror":"https://ror.org/01zvqw119"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382725322.pdf"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W1983016117","https://openalex.org/W2963150697","https://openalex.org/W2963651088","https://openalex.org/W2997004889","https://openalex.org/W3001168107","https://openalex.org/W3003732786","https://openalex.org/W3004155203","https://openalex.org/W3013954566","https://openalex.org/W3028960437","https://openalex.org/W3038668823","https://openalex.org/W3042421576","https://openalex.org/W3042556338","https://openalex.org/W3083948783","https://openalex.org/W3095247428","https://openalex.org/W3096609285","https://openalex.org/W3110932043","https://openalex.org/W3118546327","https://openalex.org/W3132252581","https://openalex.org/W3138516171","https://openalex.org/W3139633126","https://openalex.org/W3150889303","https://openalex.org/W3163465952","https://openalex.org/W3165924482","https://openalex.org/W3197486099","https://openalex.org/W3206529494","https://openalex.org/W3210586215","https://openalex.org/W3211328899","https://openalex.org/W3215638759","https://openalex.org/W3216777370","https://openalex.org/W3217153199","https://openalex.org/W4200079737","https://openalex.org/W4210839135","https://openalex.org/W4212819272","https://openalex.org/W4214520160","https://openalex.org/W4214756052","https://openalex.org/W4223970271","https://openalex.org/W4225271216","https://openalex.org/W4225295778","https://openalex.org/W4250174831","https://openalex.org/W4288834324","https://openalex.org/W4312872680","https://openalex.org/W4312881242","https://openalex.org/W4319068579","https://openalex.org/W6600783858"],"related_works":["https://openalex.org/W4390619974","https://openalex.org/W2395543297","https://openalex.org/W2163911526","https://openalex.org/W2012057384","https://openalex.org/W2189509717","https://openalex.org/W4385413143","https://openalex.org/W3162834845","https://openalex.org/W2729298216","https://openalex.org/W4210897843","https://openalex.org/W2221419418"],"abstract_inverted_index":{"Abstract":[0],"Pattern":[1],"classification":[2,45],"has":[3],"always":[4],"been":[5],"essential":[6],"in":[7,19,97],"computer":[8,20],"vision.":[9],"Transformer":[10,61,87,117,124],"paradigm":[11],"having":[12],"attention":[13],"mechanism":[14],"with":[15],"global":[16],"receptive":[17],"field":[18],"vision":[21],"improves":[22],"the":[23,42,77,102],"efficiency":[24],"and":[25,31,58,69,91,128],"effectiveness":[26],"of":[27,36,46,49,67,104],"visual":[28],"object":[29],"detection":[30],"recognition.":[32],"The":[33,72],"primary":[34],"purpose":[35],"this":[37,98],"article":[38],"is":[39,74],"to":[40,55,75],"achieve":[41],"accurate":[43],"ripeness":[44],"various":[47],"types":[48],"fruits.":[50],"We":[51,100,113],"create":[52],"fruit":[53,111],"datasets":[54],"train,":[56],"test,":[57],"evaluate":[59],"multiple":[60],"models.":[62],"Transformers":[63],"are":[64,95],"fundamentally":[65],"composed":[66],"encoding":[68],"decoding":[70],"procedures.":[71],"encoder":[73],"stack":[76],"blocks,":[78],"like":[79],"convolutional":[80],"neural":[81],"networks":[82],"(CNN":[83],"or":[84],"ConvNet).":[85],"Vision":[86],"(ViT),":[88],"Swin":[89,116],"Transformer,":[90],"multilayer":[92],"perceptron":[93],"(MLP)":[94],"considered":[96],"paper.":[99],"examine":[101],"advantages":[103],"these":[105],"three":[106],"models":[107],"for":[108,125],"accurately":[109],"analyzing":[110],"ripeness.":[112],"find":[114],"that":[115],"achieves":[118],"more":[119],"significant":[120],"outcomes":[121],"than":[122],"ViT":[123],"both":[126],"pears":[127],"apples":[129],"from":[130],"our":[131],"dataset.":[132]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}
