{"id":"https://openalex.org/W2791456092","doi":"https://doi.org/10.1109/jstars.2018.2793849","title":"Automatic Tobacco Plant Detection in UAV Images via Deep Neural Networks","display_name":"Automatic Tobacco Plant Detection in UAV Images via Deep Neural Networks","publication_year":2018,"publication_date":"2018-02-26","ids":{"openalex":"https://openalex.org/W2791456092","doi":"https://doi.org/10.1109/jstars.2018.2793849","mag":"2791456092"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2018.2793849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2793849","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5043499959","display_name":"Zhun Fan","orcid":"https://orcid.org/0000-0002-4232-8229"},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhun Fan","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Digital Signal and Image Processing, College of Engineering, Shantou University, Shantou, China"],"raw_orcid":"https://orcid.org/0000-0002-4232-8229","affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Digital Signal and Image Processing, College of Engineering, Shantou University, Shantou, China","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076499682","display_name":"Jiewei Lu","orcid":"https://orcid.org/0000-0001-5342-0939"},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiewei Lu","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Digital Signal and Image Processing, College of Engineering, Shantou University, Shantou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Digital Signal and Image Processing, College of Engineering, Shantou University, Shantou, China","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091227928","display_name":"Maoguo Gong","orcid":"https://orcid.org/0000-0002-0415-8556"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoguo Gong","raw_affiliation_strings":["Laboratory of Intelligent Perception and Image Understanding, Ministry of Education, Xidian University, Xi\u2019an, China","Laboratory of Intelligent Perception and Image Understanding, Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-0415-8556","affiliations":[{"raw_affiliation_string":"Laboratory of Intelligent Perception and Image Understanding, Ministry of Education, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Laboratory of Intelligent Perception and Image Understanding, Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090598908","display_name":"Honghui Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honghui Xie","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Digital Signal and Image Processing, College of Engineering, Shantou University, Shantou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Digital Signal and Image Processing, College of Engineering, Shantou University, Shantou, China","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034853476","display_name":"Erik D. Goodman","orcid":"https://orcid.org/0000-0002-2419-0692"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erik D. Goodman","raw_affiliation_strings":["BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-2419-0692","affiliations":[{"raw_affiliation_string":"BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":15.6147,"has_fulltext":false,"cited_by_count":108,"citation_normalized_percentile":{"value":0.98983314,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"11","issue":"3","first_page":"876","last_page":"887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9937999844551086,"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":0.9879999756813049,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7181752920150757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6974718570709229},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6935041546821594},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5655595660209656},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5056805610656738},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5051775574684143},{"id":"https://openalex.org/keywords/tobacco-leaf","display_name":"Tobacco leaf","score":0.47638386487960815},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45638683438301086},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44064462184906006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43261247873306274},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.42855194211006165},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4131573438644409},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.412834107875824},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26491665840148926},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0781075656414032}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7181752920150757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6974718570709229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6935041546821594},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5655595660209656},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5056805610656738},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5051775574684143},{"id":"https://openalex.org/C3019666931","wikidata":"https://www.wikidata.org/wiki/Q1566","display_name":"Tobacco leaf","level":2,"score":0.47638386487960815},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45638683438301086},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44064462184906006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43261247873306274},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.42855194211006165},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4131573438644409},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.412834107875824},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26491665840148926},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0781075656414032},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2018.2793849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2793849","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8799999952316284}],"awards":[],"funders":[{"id":"https://openalex.org/F4320316084","display_name":"China Computer Federation","ror":"https://ror.org/015xj5w40"},{"id":"https://openalex.org/F4320317428","display_name":"Key Lab of Digital Signal and Image Processing of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323230","display_name":"Xidian University","ror":"https://ror.org/05s92vm98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W197865394","https://openalex.org/W1513771936","https://openalex.org/W1951111310","https://openalex.org/W1955857676","https://openalex.org/W1963882359","https://openalex.org/W1968883408","https://openalex.org/W1980467157","https://openalex.org/W2004935438","https://openalex.org/W2012330712","https://openalex.org/W2016165239","https://openalex.org/W2018601649","https://openalex.org/W2023360712","https://openalex.org/W2025818287","https://openalex.org/W2043552486","https://openalex.org/W2044828101","https://openalex.org/W2058436841","https://openalex.org/W2069209512","https://openalex.org/W2072866698","https://openalex.org/W2076063813","https://openalex.org/W2081306264","https://openalex.org/W2095537868","https://openalex.org/W2099135671","https://openalex.org/W2103212315","https://openalex.org/W2106571168","https://openalex.org/W2113246181","https://openalex.org/W2118246710","https://openalex.org/W2119574220","https://openalex.org/W2123045220","https://openalex.org/W2133125644","https://openalex.org/W2136922672","https://openalex.org/W2153635508","https://openalex.org/W2154422044","https://openalex.org/W2154579312","https://openalex.org/W2157457846","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2165835468","https://openalex.org/W2327793514","https://openalex.org/W2329550497","https://openalex.org/W2412558220","https://openalex.org/W2483888092","https://openalex.org/W2535665968","https://openalex.org/W2538244214","https://openalex.org/W2919115771","https://openalex.org/W2963382180","https://openalex.org/W3122598275","https://openalex.org/W6677995690","https://openalex.org/W6682751323","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W4311401716","https://openalex.org/W2613186388","https://openalex.org/W2187221949","https://openalex.org/W2734888972","https://openalex.org/W2536634271","https://openalex.org/W4285827401","https://openalex.org/W2739874619","https://openalex.org/W4286512593","https://openalex.org/W1485614034","https://openalex.org/W3112953119"],"abstract_inverted_index":{"Tobacco":[0],"plant":[1,86,106,134,138,152],"detection":[2,68,176],"plays":[3],"an":[4,57],"important":[5],"role":[6],"in":[7,30,180],"the":[8,64,78,94,112,125,129,141,150,169,175],"management":[9],"of":[10,61,66,74,83,127,177],"tobacco":[11,28,85,105,133,178],"planting.":[12],"In":[13,77,111,140],"this":[14],"paper,":[15],"a":[16,47,81,104,108,115,160],"new":[17],"algorithm":[18,72,156,171],"based":[19],"on":[20,159,174],"deep":[21,116],"neural":[22,118],"networks":[23],"is":[24,120,145,157],"proposed":[25,71,155,170],"to":[26,147],"detect":[27],"plants":[29,179],"images":[31,43,92],"captured":[32],"by":[33,46],"unmanned":[34],"aerial":[35],"vehicles":[36],"(UAVs)":[37],"(called":[38],"UAV":[39,42,91,161,181],"images).":[40],"These":[41],"are":[44,88],"characterized":[45],"very":[48],"high":[49,59],"spatial":[50],"resolution":[51],"(35":[52],"mm),":[53],"and":[54,97,122],"consequently":[55],"contain":[56],"extremely":[58],"level":[60],"detail":[62],"for":[63],"development":[65],"automatic":[67],"algorithms.":[69],"The":[70,154,164],"consists":[73],"three":[75],"stages.":[76],"first":[79],"stage,":[80,114,143],"number":[82],"candidate":[84,101,130],"regions":[87,131,135],"extracted":[89],"from":[90],"with":[93,124],"morphological":[95],"operations":[96],"watershed":[98],"segmentation.":[99],"Each":[100],"region":[102],"contains":[103],"or":[107,136],"nontobacco":[109,137,151],"plant.":[110],"second":[113],"convolutional":[117],"network":[119],"built":[121],"trained":[123],"purpose":[126],"classifying":[128],"as":[132],"regions.":[139,153],"third":[142],"postprocessing":[144],"performed":[146],"further":[148],"remove":[149],"evaluated":[158],"image":[162],"dataset.":[163],"experimental":[165],"results":[166],"show":[167],"that":[168],"performs":[172],"well":[173],"images.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
