{"id":"https://openalex.org/W4379653946","doi":"https://doi.org/10.1117/12.2679399","title":"An efficient approach for age-wise rice seeds classification using SURF-BOF with modified cascaded-ANFIS algorithm","display_name":"An efficient approach for age-wise rice seeds classification using SURF-BOF with modified cascaded-ANFIS algorithm","publication_year":2023,"publication_date":"2023-06-07","ids":{"openalex":"https://openalex.org/W4379653946","doi":"https://doi.org/10.1117/12.2679399"},"language":"en","primary_location":{"id":"doi:10.1117/12.2679399","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2679399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth International Conference on Machine Vision (ICMV 2022)","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/A5083310775","display_name":"Namal Rathnayake","orcid":"https://orcid.org/0000-0002-5235-8552"},"institutions":[{"id":"https://openalex.org/I35568498","display_name":"Kochi University of Technology","ror":"https://ror.org/00rghrr56","country_code":"JP","type":"education","lineage":["https://openalex.org/I35568498"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Namal Rathnayake","raw_affiliation_strings":["Kochi Univ. of Technology (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kochi Univ. of Technology (Japan)","institution_ids":["https://openalex.org/I35568498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056842693","display_name":"Tuan Linh Dang","orcid":"https://orcid.org/0000-0002-9966-5576"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Tuan Linh Dang","raw_affiliation_strings":["Hanoi University of Science and Technology (Vietnam)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanoi University of Science and Technology (Vietnam)","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077841511","display_name":"Akira Miyazaki","orcid":"https://orcid.org/0000-0001-6629-3940"},"institutions":[{"id":"https://openalex.org/I77063589","display_name":"K\u014dchi University","ror":"https://ror.org/01xxp6985","country_code":"JP","type":"education","lineage":["https://openalex.org/I77063589"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Miyazaki","raw_affiliation_strings":["Kochi Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kochi Univ. (Japan)","institution_ids":["https://openalex.org/I77063589"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027658472","display_name":"Yukinobu Hoshino","orcid":"https://orcid.org/0000-0001-5285-8007"},"institutions":[{"id":"https://openalex.org/I35568498","display_name":"Kochi University of Technology","ror":"https://ror.org/00rghrr56","country_code":"JP","type":"education","lineage":["https://openalex.org/I35568498"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yukinobu Hoshino","raw_affiliation_strings":["Kochi Univ. of Technology (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kochi Univ. of Technology (Japan)","institution_ids":["https://openalex.org/I35568498"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9934,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74718123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9804999828338623,"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":0.9804999828338623,"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/T13142","display_name":"GABA and Rice Research","score":0.9718999862670898,"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/T12045","display_name":"Rice Cultivation and Yield Improvement","score":0.9180999994277954,"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/robustness","display_name":"Robustness (evolution)","score":0.7472144365310669},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"Confusion matrix","score":0.6784802675247192},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.573058545589447},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.551181435585022},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5321646928787231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5035404562950134},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.502443790435791},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4259316623210907},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36092865467071533},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3266432285308838}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7472144365310669},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.6784802675247192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.573058545589447},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.551181435585022},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5321646928787231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5035404562950134},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.502443790435791},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4259316623210907},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36092865467071533},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3266432285308838},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2679399","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2679399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth International Conference on Machine Vision (ICMV 2022)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2899196211","https://openalex.org/W2144192793","https://openalex.org/W3201472348","https://openalex.org/W3128021027","https://openalex.org/W4280636088","https://openalex.org/W3024862996","https://openalex.org/W3160713586","https://openalex.org/W1031168204","https://openalex.org/W2115329839","https://openalex.org/W4246102100"],"abstract_inverted_index":{"It":[0],"is":[1,24,91,146],"a":[2,9,16,77,88],"well-known":[3],"fact":[4],"that":[5],"the":[6,13,22,27,33,54,59,62,71,84,95,98,107,113,120,125,154,157,165,169],"quality":[7],"of":[8,15,21,26,61,97,116,138,153,168],"seed":[10,23,34,81],"highly":[11],"impacts":[12],"germination":[14],"rice":[17,49,80,117,143,161],"seed.":[18],"The":[19,64,101,136],"age":[20,163],"one":[25],"primary":[28],"key":[29],"points":[30],"in":[31,112],"assessing":[32],"quality.":[35],"Therefore,":[36],"this":[37,74],"study":[38,52],"aims":[39],"to":[40,46,70,83,93,159],"develop":[41],"an":[42],"AI-based":[43],"machine-learning":[44],"model":[45,66],"classify":[47,160],"age-wise":[48,114],"seeds.":[50,118],"This":[51],"employs":[53],"SURF-BOF-based":[55],"Cascaded-ANFIS":[56],"algorithm":[57],"for":[58],"implementation":[60],"classifier.":[63],"proposed":[65,108],"performances":[67],"were":[68,122],"compared":[69],"VGG16.":[72],"Moreover,":[73],"research":[75],"contributes":[76],"novel":[78,99],"Japanese":[79],"dataset":[82],"scientific":[85],"community.":[86],"Furthermore,":[87],"10-Fold":[89],"cross-validation":[90],"performed":[92],"evaluate":[94],"robustness":[96,111,167],"approach.":[100],"K-fold":[102],"cross-validation\u2019s":[103],"mean":[104],"accuracy":[105],"confirmed":[106],"algorithm\u2019s":[109],"higher":[110],"classification":[115,145],"Nevertheless,":[119],"results":[121,155],"evaluated":[123],"using":[124],"confusion":[126],"matrix":[127],"and":[128,134,142,150,164],"metrics":[129],"such":[130],"as":[131],"precision,":[132],"recall,":[133],"F1-Score.":[135],"Accuracy":[137],"Akitakomachi,":[139],"Koshihikari,":[140],"Yandao-8,":[141],"variety":[144],"99%,":[147,148],"92%,":[149],"97%.":[151],"Analysis":[152],"determines":[156],"ability":[158],"by":[162],"general":[166],"algorithm.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}