{"id":"https://openalex.org/W2090954818","doi":"https://doi.org/10.1631/jzus.c0910740","title":"Insect recognition based on integrated region matching and dual tree complex wavelet transform","display_name":"Insect recognition based on integrated region matching and dual tree complex wavelet transform","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W2090954818","doi":"https://doi.org/10.1631/jzus.c0910740","mag":"2090954818"},"language":"en","primary_location":{"id":"doi:10.1631/jzus.c0910740","is_oa":false,"landing_page_url":"https://doi.org/10.1631/jzus.c0910740","pdf_url":null,"source":{"id":"https://openalex.org/S199067057","display_name":"Journal of Zhejiang University SCIENCE C","issn_l":"1869-1951","issn":["1869-1951","1869-196X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311937","host_organization_name":"Zhejiang University Press","host_organization_lineage":["https://openalex.org/P4310311937"],"host_organization_lineage_names":["Zhejiang University Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Zhejiang University SCIENCE C","raw_type":"journal-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/A5111689732","display_name":"Leqing Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Le-qing Zhu","raw_affiliation_strings":["College of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, 310018, China",", Zhejiang GongShang University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, 310018, China","institution_ids":["https://openalex.org/I75059550"]},{"raw_affiliation_string":", Zhejiang GongShang University","institution_ids":["https://openalex.org/I75059550"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100622527","display_name":"Zhen Zhang","orcid":"https://orcid.org/0009-0004-6992-564X"},"institutions":[{"id":"https://openalex.org/I4210153580","display_name":"Institute of Forest Ecology, Environment and Protection","ror":"https://ror.org/05mks4240","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523","https://openalex.org/I4210153580"]},{"id":"https://openalex.org/I4210128615","display_name":"Chinese Academy of Forestry","ror":"https://ror.org/0360dkv71","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210128615","https://openalex.org/I4210134523"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Zhang","raw_affiliation_strings":["Key Lab of Forest Protection of State Forestry Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing, 100091, China","Chinese Academy of Forestry"],"affiliations":[{"raw_affiliation_string":"Key Lab of Forest Protection of State Forestry Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing, 100091, China","institution_ids":["https://openalex.org/I4210153580","https://openalex.org/I4210128615"]},{"raw_affiliation_string":"Chinese Academy of Forestry","institution_ids":["https://openalex.org/I4210128615"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111689732"],"corresponding_institution_ids":["https://openalex.org/I75059550"],"apc_list":null,"apc_paid":null,"fwci":1.2048,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.83041184,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"12","issue":"1","first_page":"44","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9968000054359436,"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":0.9968000054359436,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9929999709129333,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.961899995803833,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/complex-wavelet-transform","display_name":"Complex wavelet transform","score":0.8213198184967041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7770146131515503},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7449677586555481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6474310159683228},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5547587871551514},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.5263463258743286},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5077000856399536},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4646318554878235},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.44405972957611084},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4266257882118225},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42236945033073425},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41965562105178833},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4169459342956543},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4165993928909302},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.40755122900009155},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30391842126846313},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.21902790665626526}],"concepts":[{"id":"https://openalex.org/C2777885455","wikidata":"https://www.wikidata.org/wiki/Q5156615","display_name":"Complex wavelet transform","level":5,"score":0.8213198184967041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7770146131515503},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7449677586555481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474310159683228},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5547587871551514},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.5263463258743286},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5077000856399536},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4646318554878235},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.44405972957611084},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4266257882118225},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42236945033073425},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41965562105178833},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4169459342956543},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4165993928909302},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.40755122900009155},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30391842126846313},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.21902790665626526},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1631/jzus.c0910740","is_oa":false,"landing_page_url":"https://doi.org/10.1631/jzus.c0910740","pdf_url":null,"source":{"id":"https://openalex.org/S199067057","display_name":"Journal of Zhejiang University SCIENCE C","issn_l":"1869-1951","issn":["1869-1951","1869-196X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311937","host_organization_name":"Zhejiang University Press","host_organization_lineage":["https://openalex.org/P4310311937"],"host_organization_lineage_names":["Zhejiang University Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Zhejiang University SCIENCE C","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W182557277","https://openalex.org/W1527217146","https://openalex.org/W1606743338","https://openalex.org/W1639960393","https://openalex.org/W1952099871","https://openalex.org/W1972261560","https://openalex.org/W2016225204","https://openalex.org/W2018477907","https://openalex.org/W2051936794","https://openalex.org/W2067191022","https://openalex.org/W2109868644","https://openalex.org/W2116562978","https://openalex.org/W2121947440","https://openalex.org/W2127005096","https://openalex.org/W2129276048","https://openalex.org/W2138221429","https://openalex.org/W2162779289","https://openalex.org/W2170782121","https://openalex.org/W2184614105","https://openalex.org/W2185445531","https://openalex.org/W2602310120","https://openalex.org/W4232447660"],"related_works":["https://openalex.org/W2768918307","https://openalex.org/W115686965","https://openalex.org/W2364423108","https://openalex.org/W2040020606","https://openalex.org/W2547029902","https://openalex.org/W1983936910","https://openalex.org/W1517207589","https://openalex.org/W2205192157","https://openalex.org/W2158530844","https://openalex.org/W2147252176"],"abstract_inverted_index":{"To":[0],"provide":[1],"pest":[2],"technicians":[3],"with":[4,58,133],"a":[5,11,78,89,98,134,154],"convenient":[6],"way":[7],"to":[8,16,41,65,88,107],"recognize":[9],"insects,":[10],"novel":[12],"method":[13,130,167],"is":[14,39,50,55,85,105,119],"proposed":[15,166],"classify":[17],"insect":[18,38,139],"images":[19],"by":[20,121],"integrated":[21],"region":[22,44],"matching":[23],"(IRM)":[24],"and":[25,144],"dual":[26],"tree":[27],"complex":[28],"wavelet":[29],"transform":[30],"(DTCWT).":[31],"The":[32,53,82,102,129,161],"wing":[33],"image":[34,84],"of":[35,45,70,114,126,157,173,177],"the":[36,43,59,66,72,116,123,145,151,165,171],"lepidopteran":[37,138,178],"preprocessed":[40],"obtain":[42],"interest":[46],"(ROI)":[47],"whose":[48],"position":[49],"then":[51,86],"calibrated.":[52],"ROI":[54],"first":[56],"segmented":[57,73],"k-means":[60],"algorithm":[61],"into":[62],"regions":[63,74],"according":[64],"color":[67,83],"features,":[68],"properties":[69],"all":[71],"being":[75],"used":[76],"as":[77,97],"coarse":[79],"level":[80,100],"feature.":[81,101],"converted":[87],"grayscale":[90],"image,":[91],"where":[92],"DTCWT":[93,127],"features":[94],"are":[95],"extracted":[96],"fine":[99],"IRM":[103],"scheme":[104],"undertaken":[106],"find":[108],"K":[109],"nearest":[110,117],"neighbors":[111],"(KNNs),":[112],"out":[113],"which":[115],"neighbor":[118],"searched":[120],"computing":[122],"Canberra":[124],"distance":[125],"features.":[128],"was":[131,148,159],"tested":[132],"database":[135],"including":[136],"100":[137],"species":[140,175],"from":[141],"18":[142],"families":[143],"recognition":[146,155],"accuracy":[147,156],"84.47%.":[149],"For":[150],"forewing":[152],"subset,":[153],"92.38%":[158],"achieved.":[160],"results":[162],"showed":[163],"that":[164],"can":[168],"effectively":[169],"solve":[170],"problem":[172],"automatic":[174],"identification":[176],"specimens.":[179]},"counts_by_year":[{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}