{"id":"https://openalex.org/W2746564927","doi":"https://doi.org/10.1109/aipr.2016.8010596","title":"Convolutional neural network application to plant detection, based on synthetic imagery","display_name":"Convolutional neural network application to plant detection, based on synthetic imagery","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2746564927","doi":"https://doi.org/10.1109/aipr.2016.8010596","mag":"2746564927"},"language":"en","primary_location":{"id":"doi:10.1109/aipr.2016.8010596","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2016.8010596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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/A5055989470","display_name":"Larry Pearlstein","orcid":"https://orcid.org/0000-0001-8074-1308"},"institutions":[{"id":"https://openalex.org/I64281891","display_name":"The College of New Jersey","ror":"https://ror.org/02nx5r318","country_code":"US","type":"education","lineage":["https://openalex.org/I64281891"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Larry Pearlstein","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The College of New Jersey Ewing, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The College of New Jersey Ewing, NJ, USA","institution_ids":["https://openalex.org/I64281891"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046153438","display_name":"Mun Kim","orcid":"https://orcid.org/0000-0002-2725-2596"},"institutions":[{"id":"https://openalex.org/I64281891","display_name":"The College of New Jersey","ror":"https://ror.org/02nx5r318","country_code":"US","type":"education","lineage":["https://openalex.org/I64281891"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mun Kim","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The College of New Jersey Ewing, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The College of New Jersey Ewing, NJ, USA","institution_ids":["https://openalex.org/I64281891"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018407199","display_name":"Warren Seto","orcid":null},"institutions":[{"id":"https://openalex.org/I64281891","display_name":"The College of New Jersey","ror":"https://ror.org/02nx5r318","country_code":"US","type":"education","lineage":["https://openalex.org/I64281891"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Warren Seto","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The College of New Jersey Ewing, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The College of New Jersey Ewing, NJ, USA","institution_ids":["https://openalex.org/I64281891"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I64281891"],"apc_list":null,"apc_paid":null,"fwci":13.7626,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.98647201,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9950000047683716,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8358033895492554},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7794759273529053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.714521050453186},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.573452353477478},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5472025275230408},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5409203171730042},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.50945645570755},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4744618535041809},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.466861754655838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4553740918636322},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.44332340359687805},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4328191876411438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4067075550556183},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38319218158721924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8358033895492554},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7794759273529053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.714521050453186},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.573452353477478},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5472025275230408},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5409203171730042},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.50945645570755},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4744618535041809},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.466861754655838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4553740918636322},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.44332340359687805},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4328191876411438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4067075550556183},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38319218158721924},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr.2016.8010596","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2016.8010596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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":13,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1556850077","https://openalex.org/W1968930126","https://openalex.org/W1997395865","https://openalex.org/W2067850923","https://openalex.org/W2161684923","https://openalex.org/W2163605009","https://openalex.org/W2164699905","https://openalex.org/W2517863920","https://openalex.org/W2618530766","https://openalex.org/W2950094539","https://openalex.org/W2963801405","https://openalex.org/W4300911694"],"related_works":["https://openalex.org/W2969228573","https://openalex.org/W2952813363","https://openalex.org/W4292830139","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(DCNN's)":[4],"have":[5],"shown":[6],"great":[7],"value":[8],"in":[9,14,23,63],"approaching":[10],"highly":[11],"challenging":[12],"problems":[13],"image":[15,154],"classification.":[16],"Based":[17],"on":[18,77],"the":[19,50,56,69,72,119,124,131],"successes":[20],"of":[21,52,60,71,74,91,111,118,123,133],"DCNNs":[22,148],"scene":[24],"classification":[25],"and":[26,29,79,114,144],"object":[27],"detection":[28],"localization":[30],"it":[31],"is":[32,102,137],"natural":[33],"to":[34,55,85,108],"consider":[35],"whether":[36],"they":[37],"would":[38],"be":[39,150],"effective":[40,139,151],"for":[41,141,152],"much":[42],"simpler":[43],"computer":[44],"vision":[45],"tasks.":[46,156],"Our":[47,127],"work":[48],"involves":[49],"application":[51],"a":[53,87],"DCNN":[54],"relatively":[57],"simple":[58,153],"task":[59],"detecting":[61],"weeds":[62],"lawn":[64],"grass.":[65],"We":[66],"looked":[67],"at":[68],"effects":[70],"choice":[73],"CNN":[75],"hyper-parameters":[76],"accuracy":[78],"training":[80,112,142],"convergence":[81,125],"behavior.":[82],"In":[83],"order":[84],"obtain":[86],"large":[88],"labeled":[89],"set":[90],"interesting":[92],"data":[93],"we":[94,105],"generated":[95],"realistic":[96,134],"synthetic":[97,135],"imagery.":[98],"Since":[99],"our":[100],"problem":[101],"somewhat":[103],"constrained":[104],"were":[106],"able":[107],"run":[109],"thousands":[110],"experiments":[113],"do":[115],"accurate":[116],"estimation":[117],"probability":[120],"density":[121],"function":[122],"rate.":[126],"results":[128],"suggest":[129],"that":[130,145],"use":[132],"imagery":[136],"an":[138],"approach":[140],"DCNNs,":[143],"very":[146],"small":[147],"can":[149],"recognition":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3}],"updated_date":"2026-08-27T14:10:00.468798","created_date":"2025-10-10T00:00:00"}