{"id":"https://openalex.org/W4391384174","doi":"https://doi.org/10.3390/make6010014","title":"Real-Time Droplet Detection for Agricultural Spraying Systems: A Deep Learning Approach","display_name":"Real-Time Droplet Detection for Agricultural Spraying Systems: A Deep Learning Approach","publication_year":2024,"publication_date":"2024-01-26","ids":{"openalex":"https://openalex.org/W4391384174","doi":"https://doi.org/10.3390/make6010014"},"language":"en","primary_location":{"id":"doi:10.3390/make6010014","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6010014","pdf_url":"https://www.mdpi.com/2504-4990/6/1/14/pdf?version=1706514922","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/6/1/14/pdf?version=1706514922","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051758707","display_name":"Nhut T. Huynh","orcid":null},"institutions":[{"id":"https://openalex.org/I106959904","display_name":"Florida Institute of Technology","ror":"https://ror.org/04atsbb87","country_code":"US","type":"education","lineage":["https://openalex.org/I106959904"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nhut Huynh","raw_affiliation_strings":["Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA","institution_ids":["https://openalex.org/I106959904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062903089","display_name":"Kim\u2010Doang Nguyen","orcid":"https://orcid.org/0000-0001-6230-2432"},"institutions":[{"id":"https://openalex.org/I106959904","display_name":"Florida Institute of Technology","ror":"https://ror.org/04atsbb87","country_code":"US","type":"education","lineage":["https://openalex.org/I106959904"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kim-Doang Nguyen","raw_affiliation_strings":["Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA","institution_ids":["https://openalex.org/I106959904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062903089"],"corresponding_institution_ids":["https://openalex.org/I106959904"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":8.2228,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.97178598,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"6","issue":"1","first_page":"259","last_page":"282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12161","display_name":"Plant Surface Properties and Treatments","score":0.9977999925613403,"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/T12161","display_name":"Plant Surface Properties and Treatments","score":0.9977999925613403,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9686999917030334,"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/T12776","display_name":"Electrohydrodynamics and Fluid Dynamics","score":0.9621999859809875,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/agriculture","display_name":"Agriculture","score":0.5958795547485352},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4513874351978302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43632298707962036},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4243863821029663},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3855639696121216},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.35187265276908875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2329535186290741},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19926124811172485},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.08223786950111389}],"concepts":[{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.5958795547485352},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4513874351978302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43632298707962036},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4243863821029663},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3855639696121216},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.35187265276908875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2329535186290741},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19926124811172485},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.08223786950111389}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make6010014","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6010014","pdf_url":"https://www.mdpi.com/2504-4990/6/1/14/pdf?version=1706514922","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6dff42d918ea4f6397081e9402996130","is_oa":true,"landing_page_url":"https://doaj.org/article/6dff42d918ea4f6397081e9402996130","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 6, Iss 1, Pp 259-282 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make6010014","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6010014","pdf_url":"https://www.mdpi.com/2504-4990/6/1/14/pdf?version=1706514922","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G3977949992","display_name":null,"funder_award_id":"2022-67021-38911","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"},{"id":"https://openalex.org/G5257722410","display_name":null,"funder_award_id":"unknown","funder_id":"https://openalex.org/F4320306114","funder_display_name":"U.S. Department of Agriculture"},{"id":"https://openalex.org/G5620962805","display_name":null,"funder_award_id":"67021","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"},{"id":"https://openalex.org/G8727574970","display_name":null,"funder_award_id":"2021-67022-38910","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"}],"funders":[{"id":"https://openalex.org/F4320306114","display_name":"U.S. Department of Agriculture","ror":"https://ror.org/01na82s61"},{"id":"https://openalex.org/F4320332299","display_name":"National Institute of Food and Agriculture","ror":"https://ror.org/05qx3fv49"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4391384174.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W2084951664","https://openalex.org/W2093639510","https://openalex.org/W2154166372","https://openalex.org/W2193145675","https://openalex.org/W2486025620","https://openalex.org/W2613718673","https://openalex.org/W2615202364","https://openalex.org/W2789518880","https://openalex.org/W2900463373","https://openalex.org/W2907372163","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2981281324","https://openalex.org/W3013314912","https://openalex.org/W3042011474","https://openalex.org/W3096832794","https://openalex.org/W3106250896","https://openalex.org/W3127722140","https://openalex.org/W3210586215","https://openalex.org/W4200070037","https://openalex.org/W4205382760","https://openalex.org/W4214935340","https://openalex.org/W4221034033","https://openalex.org/W4221070396","https://openalex.org/W4295953483","https://openalex.org/W4297474673","https://openalex.org/W4304115958","https://openalex.org/W4383752296","https://openalex.org/W4388520256","https://openalex.org/W6757072215"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W2939353110","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756"],"abstract_inverted_index":{"Nozzles":[0],"are":[1,6,24],"ubiquitous":[2],"in":[3,117,171,190,203],"agriculture:":[4],"they":[5],"used":[7],"to":[8,15,52,70,75,90,98],"spray":[9,40,50],"and":[10,13,36,42,55,114,144,161,181,187],"apply":[11],"nutrients":[12],"pesticides":[14],"crops.":[16],"The":[17,120,147,163,193],"properties":[18,74],"of":[19,31,48,79,125,154,157,179],"droplets":[20,92,156],"sprayed":[21],"from":[22],"nozzles":[23],"vital":[25],"factors":[26],"that":[27,61,109,167],"determine":[28],"the":[29,32,49,53,63,77,152,168,176],"effectiveness":[30],"spray.":[33],"Droplet":[34],"size":[35],"other":[37],"characteristics":[38],"affect":[39],"retention":[41],"drift,":[43],"which":[44],"indicates":[45],"how":[46,56],"much":[47,57],"adheres":[51],"crop":[54,80],"becomes":[58],"chemical":[59],"runoff":[60],"pollutes":[62],"environment.":[64],"There":[65],"is":[66,104,149],"a":[67,86,95,123,138,184,200],"critical":[68],"need":[69],"measure":[71,99],"these":[72],"droplet":[73,191,204],"improve":[76],"performance":[78],"spraying":[81],"systems.":[82],"This":[83,102],"paper":[84],"establishes":[85],"deep":[87],"learning":[88],"methodology":[89,195],"detect":[91],"moving":[93],"across":[94],"camera":[96],"frame":[97],"their":[100],"size.":[101],"framework":[103],"compatible":[105],"with":[106,151,175],"embedded":[107],"systems":[108],"have":[110],"limited":[111],"onboard":[112],"resources":[113],"can":[115],"operate":[116],"real":[118],"time.":[119],"method":[121],"leverages":[122],"combination":[124,178],"techniques":[126],"including":[127],"resizing,":[128],"normalization,":[129],"pruning,":[130],"detection":[131,205],"head,":[132],"unified":[133],"feature":[134,139],"map":[135],"extraction":[136],"via":[137],"pyramid":[140],"network,":[141],"non-maximum":[142],"suppression,":[143],"optimization-based":[145],"training.":[146],"approach":[148],"designed":[150,170],"capability":[153],"detecting":[155],"various":[158],"sizes,":[159],"shapes,":[160],"orientations.":[162],"experimental":[164],"results":[165],"demonstrate":[166],"model":[169],"this":[172],"study,":[173],"coupled":[174],"right":[177],"dataset":[180],"augmentation,":[182],"achieved":[183],"97%":[185],"precision":[186,207],"96.8%":[188],"recall":[189],"detection.":[192],"proposed":[194],"outperformed":[196],"previous":[197],"models,":[198],"marking":[199],"significant":[201],"advancement":[202],"for":[206],"agriculture":[208],"applications.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}