{"id":"https://openalex.org/W2786808496","doi":"https://doi.org/10.1109/iccsce.2017.8284406","title":"Performance effect analysis for insect classification using convolutional neural network","display_name":"Performance effect analysis for insect classification using convolutional neural network","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2786808496","doi":"https://doi.org/10.1109/iccsce.2017.8284406","mag":"2786808496"},"language":"en","primary_location":{"id":"doi:10.1109/iccsce.2017.8284406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccsce.2017.8284406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","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/A5007358895","display_name":"Su-Chang Lim","orcid":"https://orcid.org/0009-0009-4891-4745"},"institutions":[{"id":"https://openalex.org/I199143407","display_name":"Sunchon National University","ror":"https://ror.org/043jqrs76","country_code":"KR","type":"education","lineage":["https://openalex.org/I199143407"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Suchang Lim","raw_affiliation_strings":["Dept. Computer Engineering, Sunchon National University, Sunchon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Computer Engineering, Sunchon National University, Sunchon, Republic of Korea","institution_ids":["https://openalex.org/I199143407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100454615","display_name":"Seung Hyun Kim","orcid":"https://orcid.org/0000-0001-9644-9598"},"institutions":[{"id":"https://openalex.org/I199143407","display_name":"Sunchon National University","ror":"https://ror.org/043jqrs76","country_code":"KR","type":"education","lineage":["https://openalex.org/I199143407"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seunghyun Kim","raw_affiliation_strings":["Dept. Computer Engineering, Sunchon National University, Sunchon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Computer Engineering, Sunchon National University, Sunchon, Republic of Korea","institution_ids":["https://openalex.org/I199143407"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100652838","display_name":"Doyeon Kim","orcid":"https://orcid.org/0000-0003-3717-7275"},"institutions":[{"id":"https://openalex.org/I199143407","display_name":"Sunchon National University","ror":"https://ror.org/043jqrs76","country_code":"KR","type":"education","lineage":["https://openalex.org/I199143407"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Doyeon Kim","raw_affiliation_strings":["Dept. Computer Engineering, Sunchon National University, Sunchon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Computer Engineering, Sunchon National University, Sunchon, Republic of Korea","institution_ids":["https://openalex.org/I199143407"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.5712,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.95146755,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"210","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9700999855995178,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9635000228881836,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8198868632316589},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7536660432815552},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.7407160997390747},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7160665988922119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7086817622184753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6990209221839905},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5202751755714417},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46133482456207275},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4329304099082947},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4157865047454834}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8198868632316589},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7536660432815552},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.7407160997390747},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7160665988922119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7086817622184753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6990209221839905},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5202751755714417},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46133482456207275},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4329304099082947},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4157865047454834}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccsce.2017.8284406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccsce.2017.8284406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334881","display_name":"Korea Forest Service","ror":"https://ror.org/05bjbww34"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W189270827","https://openalex.org/W1517347710","https://openalex.org/W1561161063","https://openalex.org/W1596717185","https://openalex.org/W1952099871","https://openalex.org/W1955003279","https://openalex.org/W2016225204","https://openalex.org/W2035677848","https://openalex.org/W2076063813","https://openalex.org/W2085253271","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2146248736","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2564288310","https://openalex.org/W4250664506","https://openalex.org/W6607679968","https://openalex.org/W6676297131","https://openalex.org/W6681524037","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W2964843961"],"abstract_inverted_index":{"It":[0],"is":[1],"necessary":[2],"to":[3,12,41],"develop":[4],"an":[5],"automated":[6],"insect":[7,73],"classification":[8,21,31,50,84],"method":[9],"in":[10,58],"order":[11],"create":[13],"high":[14],"added":[15],"value":[16],"of":[17,30,48,56,75,86,98,105],"insects.":[18],"Recently,":[19],"image":[20,66],"work":[22],"applying":[23],"deep":[24],"learning":[25],"shows":[26],"the":[27,46,49,53,59,64,83,96,99,103],"best":[28],"result":[29],"performance.":[32],"In":[33],"this":[34],"paper,":[35],"we":[36],"use":[37],"convolutional":[38],"neural":[39,87],"network":[40,88],"classify":[42],"insects":[43,91],"and":[44,62,101],"examine":[45],"effect":[47],"performance":[51,85],"with":[52,63,78],"varying":[54],"number":[55,104],"kernels":[57,107],"convolution":[60,106],"layer":[61],"different":[65],"datasets.":[67],"Experiments":[68],"were":[69],"conducted":[70],"on":[71],"27":[72],"classes":[74],"ImageNet":[76],"dataset":[77],"AlexNet.":[79],"We":[80],"confirmed":[81],"that":[82],"improves":[89],"where":[90],"are":[92],"well":[93],"represented":[94],"at":[95],"center":[97],"image,":[100],"when":[102],"increases.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
