{"id":"https://openalex.org/W4283264637","doi":"https://doi.org/10.1145/3529836.3529850","title":"Apple Leaf Disease Recognition Based on Attention Mechanics and Multi-Scale Feature Fusion","display_name":"Apple Leaf Disease Recognition Based on Attention Mechanics and Multi-Scale Feature Fusion","publication_year":2022,"publication_date":"2022-02-18","ids":{"openalex":"https://openalex.org/W4283264637","doi":"https://doi.org/10.1145/3529836.3529850"},"language":"en","primary_location":{"id":"doi:10.1145/3529836.3529850","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3529836.3529850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","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/A5054511681","display_name":"Hankun Chai","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hankun Chai","raw_affiliation_strings":["School of Imformation Engineering, Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Imformation Engineering, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052043342","display_name":"Zhiqiang Guo","orcid":"https://orcid.org/0000-0003-1659-2445"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Guo","raw_affiliation_strings":["School of Imformation Engineering, Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Imformation Engineering, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109235166","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0001-9121-5581"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["School of Imformation Engineering, Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Imformation Engineering, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054511681"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":1.4624,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83349451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"368","last_page":"374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9571999907493591,"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":0.9545999765396118,"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":0.6885144710540771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6743075251579285},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6531938314437866},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6383842825889587},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6309138536453247},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6299507021903992},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5507156848907471},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5070369243621826},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45712772011756897},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43652400374412537},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4275633692741394},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.410930335521698},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2555058002471924},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21958449482917786}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6885144710540771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6743075251579285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6531938314437866},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6383842825889587},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6309138536453247},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6299507021903992},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5507156848907471},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5070369243621826},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45712772011756897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43652400374412537},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4275633692741394},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.410930335521698},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2555058002471924},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21958449482917786},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3529836.3529850","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3529836.3529850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Machine Learning and Computing (ICMLC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.5,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2400429454","https://openalex.org/W2549139847","https://openalex.org/W2752782242","https://openalex.org/W2884585870","https://openalex.org/W2934580386","https://openalex.org/W2963504571","https://openalex.org/W2980677578","https://openalex.org/W3011313660","https://openalex.org/W3036111160","https://openalex.org/W3088127670","https://openalex.org/W3162474807","https://openalex.org/W3177052299","https://openalex.org/W7033828139"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2108418243","https://openalex.org/W164103134","https://openalex.org/W2787352659","https://openalex.org/W1970611213","https://openalex.org/W1707372784","https://openalex.org/W1996690921"],"abstract_inverted_index":{"Early":[0],"diagnosis":[1,21],"and":[2,16,22,51,91,145,163,167,181,186,194,216],"accurate":[3],"identification":[4,23],"of":[5,24,38,55,99,141,159,178],"apple":[6,25,46,83,220],"diseases":[7,26,57],"play":[8],"a":[9,113,127,212],"major":[10],"role":[11,158],"in":[12,30,41,108,152,224],"reducing":[13],"growing":[14],"costs":[15],"curbing":[17],"economic":[18],"losses.":[19],"The":[20,150,204],"are":[27],"more":[28,67],"difficult":[29,68],"the":[31,53,96,105,109,134,139,142,147,157,160,172,176,187,195,199,208,225],"natural":[32,43,226],"farming":[33],"environment.":[34,227],"A":[35,60],"large":[36],"amount":[37],"background":[39],"noise":[40,192],"complex":[42],"environments":[44],"makes":[45,52],"disease":[47,143,222],"features":[48,54,144],"relatively":[49],"inconspicuous":[50],"different":[56],"less":[58],"distinguishable.":[59],"single-scale":[61],"feature":[62,93],"extraction":[63],"network":[64,86],"will":[65],"be":[66],"to":[69,75,121,133,137],"extract":[70],"effective":[71],"information.":[72],"In":[73],"order":[74],"solve":[76],"this":[77,79,153],"problem,":[78],"paper":[80,154],"proposes":[81],"an":[82],"leaf":[84,221],"classification":[85,148,196,214],"based":[87],"on":[88,198],"attention":[89,129,161,179],"mechanism":[90,162,180],"multi-scale":[92,123],"fusion.":[94],"First,":[95],"residual":[97,110,135],"unit":[98,111],"ResNet50":[100],"is":[101,131,184,202],"improved":[102],"by":[103,117],"replacing":[104],"second":[106],"convolution":[107,115,120,165,183],"with":[112],"pyramidal":[114,164,182],"modified":[116],"using":[118],"dilated":[119],"obtain":[122],"fused":[124],"features.":[125],"Then":[126,175],"channel":[128],"module":[130],"added":[132],"bypass":[136],"enhance":[138],"weighting":[140],"improve":[146,171],"accuracy.":[149],"experiments":[151],"first":[155],"validate":[156],"separately":[166],"find":[168],"that":[169,207],"both":[170],"model":[173,189,210],"performance.":[174],"combination":[177],"validated,":[185],"optimized":[188,209],"has":[190,211],"stronger":[191],"immunity":[193],"accuracy":[197],"validation":[200],"set":[201],"94.96%.":[203],"results":[205],"show":[206],"better":[213],"effect":[215],"higher":[217],"robustness":[218],"for":[219],"pictures":[223]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
