{"id":"https://openalex.org/W4362564729","doi":"https://doi.org/10.1145/3579895.3579915","title":"Apple Counting Network Before Fruit Thinning Period Based On Dilated Convolution","display_name":"Apple Counting Network Before Fruit Thinning Period Based On Dilated Convolution","publication_year":2022,"publication_date":"2022-12-09","ids":{"openalex":"https://openalex.org/W4362564729","doi":"https://doi.org/10.1145/3579895.3579915"},"language":"en","primary_location":{"id":"doi:10.1145/3579895.3579915","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3579895.3579915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Networks, Communication and Computing","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/A5045528702","display_name":"Mengyang Song","orcid":"https://orcid.org/0000-0002-9504-9178"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengyang Song","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0002-9504-9178","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002373133","display_name":"Guoquan Jiang","orcid":"https://orcid.org/0000-0002-8729-0017"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoquan Jiang","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0002-8729-0017","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017764646","display_name":"Zhanqiang Huo","orcid":"https://orcid.org/0000-0001-9243-5009"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanqiang Huo","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0001-9243-5009","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039206087","display_name":"Zhengyuan Yang","orcid":"https://orcid.org/0000-0002-6970-0123"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyuan Yang","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0002-6970-0123","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072185862","display_name":"Hongxu Zhang","orcid":"https://orcid.org/0000-0003-2549-3131"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxu Zhang","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0003-2549-3131","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210166499"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29387672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":null,"first_page":"129","last_page":"134"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9739999771118164,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/orchard","display_name":"Orchard","score":0.7023290991783142},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5522032380104065},{"id":"https://openalex.org/keywords/thinning","display_name":"Thinning","score":0.5235719084739685},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5219237804412842},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5174230337142944},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4300180971622467},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.42935389280319214},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4217136800289154},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3864486515522003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3649634122848511},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33327198028564453},{"id":"https://openalex.org/keywords/horticulture","display_name":"Horticulture","score":0.12299138307571411},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.102110356092453},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.07245528697967529}],"concepts":[{"id":"https://openalex.org/C2780753983","wikidata":"https://www.wikidata.org/wiki/Q236371","display_name":"Orchard","level":2,"score":0.7023290991783142},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5522032380104065},{"id":"https://openalex.org/C2781353100","wikidata":"https://www.wikidata.org/wiki/Q1266974","display_name":"Thinning","level":2,"score":0.5235719084739685},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5219237804412842},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5174230337142944},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4300180971622467},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.42935389280319214},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4217136800289154},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3864486515522003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3649634122848511},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33327198028564453},{"id":"https://openalex.org/C144027150","wikidata":"https://www.wikidata.org/wiki/Q48803","display_name":"Horticulture","level":1,"score":0.12299138307571411},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.102110356092453},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.07245528697967529},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3579895.3579915","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3579895.3579915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Networks, Communication and Computing","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":21,"referenced_works":["https://openalex.org/W1910776219","https://openalex.org/W1980623462","https://openalex.org/W2108598243","https://openalex.org/W2543665758","https://openalex.org/W2555576940","https://openalex.org/W2625680238","https://openalex.org/W2788040570","https://openalex.org/W2902549641","https://openalex.org/W2946332037","https://openalex.org/W2955171701","https://openalex.org/W2964436429","https://openalex.org/W2964648978","https://openalex.org/W2967161970","https://openalex.org/W3043115696","https://openalex.org/W3046073559","https://openalex.org/W3101500023","https://openalex.org/W3110407708","https://openalex.org/W4210248601","https://openalex.org/W4224923734","https://openalex.org/W6735463952","https://openalex.org/W6756774705"],"related_works":["https://openalex.org/W2357280244","https://openalex.org/W4283836740","https://openalex.org/W1573752787","https://openalex.org/W2072657584","https://openalex.org/W2989655533","https://openalex.org/W2350998906","https://openalex.org/W2375223689","https://openalex.org/W2085241531","https://openalex.org/W2337991629","https://openalex.org/W4311457544"],"abstract_inverted_index":{"Abstract:":[0],"Fruit":[1],"counting":[2,13,52,59],"is":[3,54,62,77,121,125],"an":[4],"integral":[5],"part":[6],"of":[7,14,17,68,92],"achieving":[8],"precision":[9,31],"orchard":[10],"management.":[11],"Accurate":[12],"the":[15,66,80,90,100,119,123],"number":[16],"fruits":[18],"on":[19,79,99],"a":[20,46],"tree":[21],"can":[22,37,128],"provide":[23],"critical":[24],"information":[25],"for":[26,139],"yield":[27],"estimation,":[28],"thus":[29],"promoting":[30],"agriculture.":[32],"However,":[33],"today":[34],"fruit":[35,51,73],"farmers":[36],"only":[38],"support":[39],"their":[40],"fieldwork":[41],"by":[42],"manual":[43],"counting,":[44],"and":[45,48,72,76,110,127],"reliable":[47],"accurate":[49],"automatic":[50],"method":[53,84],"missing.":[55],"A":[56],"pre-thinning":[57],"apple":[58],"network":[60],"(FTACNet)":[61],"proposed":[63],"to":[64,108,116,132],"address":[65],"problems":[67],"shading,":[69],"uneven":[70],"distribution,":[71],"scale":[74],"differences":[75],"validated":[78],"produced":[81],"dataset.":[82],"The":[83],"uses":[85],"deep":[86],"learning":[87],"algorithms":[88],"in":[89,141],"field":[91],"population":[93],"counting.":[94],"FTACNet":[95],"shows":[96],"good":[97,137],"performance":[98],"dataset,":[101],"with":[102],"mean":[103,111],"absolute":[104],"error":[105,113],"(MAE)":[106],"down":[107,115],"4.14":[109],"square":[112],"(MSE)":[114],"5.62.":[117],"Moreover,":[118],"model":[120,124],"end-to-end,":[122],"small,":[126],"be":[129],"easily":[130],"deployed":[131],"mobile":[133],"devices,":[134],"which":[135],"has":[136],"potential":[138],"application":[140],"orchards.":[142]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}