{"id":"https://openalex.org/W2914706761","doi":"https://doi.org/10.1109/icdsp.2018.8631562","title":"Fruit Classification Based on Six Layer Convolutional Neural Network","display_name":"Fruit Classification Based on Six Layer Convolutional Neural Network","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2914706761","doi":"https://doi.org/10.1109/icdsp.2018.8631562","mag":"2914706761"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2018.8631562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","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/A5028974886","display_name":"Siyuan Lu","orcid":"https://orcid.org/0000-0001-6720-1323"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Siyuan Lu","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Jiangsu, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046739709","display_name":"Zhihai Lu","orcid":"https://orcid.org/0000-0001-5271-4281"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihai Lu","raw_affiliation_strings":["School of Education Science, Nanjing Normal University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Education Science, Nanjing Normal University, Jiangsu, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044153933","display_name":"Soriya Aok","orcid":null},"institutions":[{"id":"https://openalex.org/I3130157972","display_name":"Angkor University","ror":"https://ror.org/0071art98","country_code":"KH","type":"education","lineage":["https://openalex.org/I3130157972"]},{"id":"https://openalex.org/I186365177","display_name":"Institute of Technology of Cambodia","ror":"https://ror.org/054z67s11","country_code":"KH","type":"education","lineage":["https://openalex.org/I186365177"]}],"countries":["KH"],"is_corresponding":false,"raw_author_name":"Soriya Aok","raw_affiliation_strings":["Faculty of Science and Technology, Angkor University, Borey Seang Nam, Siem Reap Province, Cambodia"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Angkor University, Borey Seang Nam, Siem Reap Province, Cambodia","institution_ids":["https://openalex.org/I3130157972","https://openalex.org/I186365177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036694605","display_name":"Logan Graham","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Logan Graham","raw_affiliation_strings":["Department of Mathematics, Ryerson University, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Ryerson University, Toronto, ON, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028974886"],"corresponding_institution_ids":["https://openalex.org/I152031979"],"apc_list":null,"apc_paid":null,"fwci":6.2702,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.95886822,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9975000023841858,"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":0.9975000023841858,"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":0.9909999966621399,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.95169997215271,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.767289936542511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7556993365287781},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7546839714050293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.676902174949646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6696996688842773},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5195487141609192},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.47034385800361633},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.43540796637535095},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4256709814071655},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3617839217185974}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.767289936542511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7556993365287781},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7546839714050293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.676902174949646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6696996688842773},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5195487141609192},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.47034385800361633},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.43540796637535095},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4256709814071655},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3617839217185974},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdsp.2018.8631562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1672221038","https://openalex.org/W1912141599","https://openalex.org/W1933512202","https://openalex.org/W1949503316","https://openalex.org/W1963939054","https://openalex.org/W2002996870","https://openalex.org/W2010110404","https://openalex.org/W2055957015","https://openalex.org/W2060117429","https://openalex.org/W2075478651","https://openalex.org/W2083474188","https://openalex.org/W2109209964","https://openalex.org/W2156580010","https://openalex.org/W2174673307","https://openalex.org/W2175649320","https://openalex.org/W2286295202","https://openalex.org/W2298616966","https://openalex.org/W2410006390","https://openalex.org/W2474408364","https://openalex.org/W2485371228","https://openalex.org/W2490767898","https://openalex.org/W2582442958","https://openalex.org/W2605260836","https://openalex.org/W2620081215","https://openalex.org/W2745034183","https://openalex.org/W2745482664","https://openalex.org/W2754586266","https://openalex.org/W2758007480","https://openalex.org/W2763397241","https://openalex.org/W2770131355","https://openalex.org/W2774054169","https://openalex.org/W2788663687","https://openalex.org/W2790012920","https://openalex.org/W2792998389","https://openalex.org/W2801165650","https://openalex.org/W2801391419","https://openalex.org/W3151941575"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W147410782","https://openalex.org/W4287804464","https://openalex.org/W3022252430","https://openalex.org/W2810679507","https://openalex.org/W2964954556","https://openalex.org/W4291617047","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Automatic":[0],"fruit":[1,32],"classification":[2],"is":[3],"a":[4,36],"difficult":[5],"problem":[6],"because":[7],"there":[8],"are":[9],"so":[10],"many":[11],"types":[12],"of":[13,40,61],"fruits":[14],"and":[15,45,74],"the":[16],"large":[17],"inter-class":[18],"similarity.":[19],"In":[20],"this":[21],"study,":[22],"we":[23],"proposed":[24],"to":[25],"use":[26],"convolutional":[27],"neural":[28],"network":[29],"(CNN)":[30],"for":[31],"classification.":[33],"We":[34],"designed":[35],"six-layer":[37],"CNN":[38],"consisting":[39],"convolution":[41],"layers,":[42],"pooling":[43],"layers":[44],"fully":[46],"connected":[47],"layers.":[48],"The":[49],"experiment":[50],"results":[51],"suggested":[52],"that":[53],"our":[54],"method":[55],"achieved":[56],"promising":[57],"performance":[58],"with":[59],"accuracy":[60],"91.44%,":[62],"better":[63],"than":[64],"three":[65],"state-of-the-art":[66],"approaches:":[67],"voting-based":[68],"support":[69],"vector":[70],"machine,":[71],"wavelet":[72],"entropy,":[73],"genetic":[75],"algorithm.":[76]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
