{"id":"https://openalex.org/W2988063103","doi":"https://doi.org/10.1109/access.2019.2952176","title":"Plant Species Recognition Using Morphological Features and Adaptive Boosting Methodology","display_name":"Plant Species Recognition Using Morphological Features and Adaptive Boosting Methodology","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2988063103","doi":"https://doi.org/10.1109/access.2019.2952176","mag":"2988063103"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2952176","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2952176","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2019.2952176","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055589318","display_name":"Munish Kumar","orcid":"https://orcid.org/0000-0003-0115-1620"},"institutions":[{"id":"https://openalex.org/I4210136518","display_name":"Maharaja Ranjit Singh Punjab Technical University","ror":"https://ror.org/03k7qz240","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210136518"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Munish Kumar","raw_affiliation_strings":["Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India"],"raw_orcid":"https://orcid.org/0000-0003-0115-1620","affiliations":[{"raw_affiliation_string":"Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India","institution_ids":["https://openalex.org/I4210136518"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075521683","display_name":"Surbhi Gupta","orcid":"https://orcid.org/0000-0003-0618-8369"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Surbhi Gupta","raw_affiliation_strings":["Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India"],"raw_orcid":"https://orcid.org/0000-0003-0618-8369","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003491781","display_name":"Xiao\u2010Zhi Gao","orcid":"https://orcid.org/0000-0002-0078-5675"},"institutions":[{"id":"https://openalex.org/I175532246","display_name":"University of Eastern Finland","ror":"https://ror.org/00cyydd11","country_code":"FI","type":"education","lineage":["https://openalex.org/I175532246"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Xiao-Zhi Gao","raw_affiliation_strings":["School of Computing, University of Eastern Finland, Kuopio, Finland"],"raw_orcid":"https://orcid.org/0000-0002-0078-5675","affiliations":[{"raw_affiliation_string":"School of Computing, University of Eastern Finland, Kuopio, Finland","institution_ids":["https://openalex.org/I175532246"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085144343","display_name":"Amitoj Singh","orcid":"https://orcid.org/0000-0002-5884-3145"},"institutions":[{"id":"https://openalex.org/I4210136518","display_name":"Maharaja Ranjit Singh Punjab Technical University","ror":"https://ror.org/03k7qz240","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210136518"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amitoj Singh","raw_affiliation_strings":["Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India"],"raw_orcid":"https://orcid.org/0000-0002-5884-3145","affiliations":[{"raw_affiliation_string":"Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India","institution_ids":["https://openalex.org/I4210136518"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.5942,"has_fulltext":false,"cited_by_count":98,"citation_normalized_percentile":{"value":0.98251852,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"163912","last_page":"163918"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9988999962806702,"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":0.9988999962806702,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9574999809265137,"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":0.9361000061035156,"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":0.820331871509552},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6474752426147461},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6446212530136108},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6274274587631226},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.5553167462348938},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5527608394622803},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.5235801935195923},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4925137460231781},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.43566587567329407},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.43182075023651123},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.41879206895828247},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.41505166888237},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38966310024261475},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26437729597091675},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10003632307052612}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.820331871509552},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474752426147461},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6446212530136108},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6274274587631226},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.5553167462348938},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5527608394622803},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.5235801935195923},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4925137460231781},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.43566587567329407},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.43182075023651123},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41879206895828247},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.41505166888237},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38966310024261475},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26437729597091675},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10003632307052612}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2952176","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2952176","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:15bf3c312aa746c1a2d259188220da93","is_oa":true,"landing_page_url":"https://doaj.org/article/15bf3c312aa746c1a2d259188220da93","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 163912-163918 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2952176","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2952176","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W143093700","https://openalex.org/W1570646234","https://openalex.org/W1965574957","https://openalex.org/W1968896562","https://openalex.org/W2012093028","https://openalex.org/W2030432742","https://openalex.org/W2066312471","https://openalex.org/W2069203968","https://openalex.org/W2081882777","https://openalex.org/W2098205315","https://openalex.org/W2105058780","https://openalex.org/W2117405177","https://openalex.org/W2119522318","https://openalex.org/W2123507580","https://openalex.org/W2126283961","https://openalex.org/W2131768008","https://openalex.org/W2136915956","https://openalex.org/W2142977429","https://openalex.org/W2145073242","https://openalex.org/W2155323527","https://openalex.org/W2170049341","https://openalex.org/W2187353335","https://openalex.org/W2241490242","https://openalex.org/W2275793951","https://openalex.org/W2280927682","https://openalex.org/W2305974450","https://openalex.org/W2414372613","https://openalex.org/W2606091860","https://openalex.org/W2616728375","https://openalex.org/W2788204912","https://openalex.org/W6605853681","https://openalex.org/W6641350041","https://openalex.org/W6674697053","https://openalex.org/W6677597731","https://openalex.org/W6677807493","https://openalex.org/W6678912888","https://openalex.org/W6680903806","https://openalex.org/W6681651645","https://openalex.org/W6682707635","https://openalex.org/W6687112924","https://openalex.org/W6694319020","https://openalex.org/W6697988043","https://openalex.org/W6715487673","https://openalex.org/W6998677455"],"related_works":["https://openalex.org/W2381926679","https://openalex.org/W2007009951","https://openalex.org/W2082644203","https://openalex.org/W4387977367","https://openalex.org/W2141272333","https://openalex.org/W2994772185","https://openalex.org/W2011666252","https://openalex.org/W1528227026","https://openalex.org/W4386970085","https://openalex.org/W4214940564"],"abstract_inverted_index":{"Plant":[0],"species":[1,64],"detection":[2],"aims":[3],"at":[4],"the":[5,23,29,46,68,103,125,146,149,157,161,188,195],"automatic":[6],"identification":[7],"of":[8,13,45,70,128,131,148,160,182],"plants.":[9],"Although":[10],"a":[11,33,61,74,99,169],"lot":[12],"aspects":[14],"like":[15],"leaf,":[16],"flowers,":[17],"fruits,":[18],"seeds":[19],"could":[20],"contribute":[21],"to":[22,42,51,96,144],"decision,":[24],"but":[25],"leaf":[26,35,100],"features":[27,72],"are":[28,94,122,142,166],"most":[30],"significant.":[31],"As":[32],"plant":[34,55,63],"is":[36,49,153],"always":[37],"more":[38],"accessible":[39],"as":[40],"compared":[41],"other":[43],"parts":[44],"plants,":[47],"it":[48,53],"obvious":[50],"study":[52],"for":[54,102,155],"identification.":[56],"The":[57,79],"present":[58],"paper":[59],"introduced":[60],"novel":[62],"classifier":[65],"based":[66],"on":[67,168],"extraction":[69,105],"morphological":[71,108],"using":[73,187],"Multilayer":[75,140],"Perceptron":[76],"with":[77],"Adaboosting.":[78],"proposed":[80,162,189],"framework":[81],"comprises":[82],"pre-processing,":[83],"feature":[84,86,104],"extraction,":[85],"selection,":[87],"and":[88,120,139],"classification.":[89],"Initially,":[90],"some":[91],"pre-processing":[92],"techniques":[93],"used":[95],"set":[97],"up":[98],"image":[101],"process.":[106],"Various":[107],"features,":[109],"i.e.,":[110,135],"centroid,":[111],"major":[112],"axis":[113,116],"length,":[114,117],"minor":[115],"solidity,":[118],"perimeter,":[119],"orientation":[121],"extracted":[123],"from":[124,174],"digital":[126],"images":[127],"various":[129],"categories":[130],"leaves.":[132],"Different":[133],"classifiers,":[134],"k-NN,":[136],"Decision":[137],"Tree":[138],"perceptron":[141],"employed":[143],"test":[145],"accuracy":[147],"algorithm.":[150],"AdaBoost":[151],"methodology":[152],"explored":[154],"improving":[156],"precision":[158,180],"rate":[159,181],"system.":[163],"Experimental":[164],"results":[165],"obtained":[167],"public":[170],"dataset":[171],"(FLAVIA)":[172],"downloaded":[173],"<uri":[175],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[176],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">http://flavia.sourceforge.net/</uri>":[177],".":[178],"A":[179],"95.42%":[183],"has":[184],"been":[185],"achieved":[186],"machine":[190],"learning":[191],"classifier,":[192],"which":[193],"outperformed":[194],"state-of-the-art":[196],"algorithms.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":4}],"updated_date":"2026-06-14T07:44:22.658603","created_date":"2025-10-10T00:00:00"}
