{"id":"https://openalex.org/W1577901045","doi":"https://doi.org/10.1109/retis.2015.7232876","title":"Recognition of whole and deformed plant leaves using statistical shape features and neuro-fuzzy classifier","display_name":"Recognition of whole and deformed plant leaves using statistical shape features and neuro-fuzzy classifier","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1577901045","doi":"https://doi.org/10.1109/retis.2015.7232876","mag":"1577901045"},"language":"en","primary_location":{"id":"doi:10.1109/retis.2015.7232876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/retis.2015.7232876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS)","raw_type":"proceedings-article"},"type":"article","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/A5090666420","display_name":"Jyotismita Chaki","orcid":"https://orcid.org/0000-0003-1804-8590"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jyotismita Chaki","raw_affiliation_strings":["School of Education Technology, Jadavpur University, Kolkata, India","School of Education Technology, Jadavpur University Kolkata, India"],"affiliations":[{"raw_affiliation_string":"School of Education Technology, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"School of Education Technology, Jadavpur University Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005250411","display_name":"Ranjan Parekh","orcid":null},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ranjan Parekh","raw_affiliation_strings":["School of Education Technology, Jadavpur University, Kolkata, India","School of Education Technology, Jadavpur University Kolkata, India"],"affiliations":[{"raw_affiliation_string":"School of Education Technology, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"School of Education Technology, Jadavpur University Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110468302","display_name":"Samar Bhattacharya","orcid":null},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Samar Bhattacharya","raw_affiliation_strings":["School of Education Technology, Jadavpur University, Kolkata, India","Dept. of Electrical Engg., Jadavpur University Kolkata, India"],"affiliations":[{"raw_affiliation_string":"School of Education Technology, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"Dept. of Electrical Engg., Jadavpur University Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090666420"],"corresponding_institution_ids":["https://openalex.org/I170979836"],"apc_list":null,"apc_paid":null,"fwci":3.5406,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.91840354,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"41","issue":null,"first_page":"189","last_page":"194"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9983000159263611,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9983000159263611,"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":0.998199999332428,"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":0.9800999760627747,"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":0.753258466720581},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7282216548919678},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.642722487449646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5594108700752258},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5438587665557861},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5178749561309814},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5031136870384216},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4599081873893738},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.4376979470252991},{"id":"https://openalex.org/keywords/geometric-shape","display_name":"Geometric shape","score":0.4120347201824188},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.40439581871032715},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3535916805267334},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35288575291633606},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10512542724609375}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.753258466720581},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7282216548919678},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.642722487449646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5594108700752258},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5438587665557861},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5178749561309814},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5031136870384216},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4599081873893738},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.4376979470252991},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.4120347201824188},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.40439581871032715},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3535916805267334},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35288575291633606},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10512542724609375},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/retis.2015.7232876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/retis.2015.7232876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W121282825","https://openalex.org/W159932088","https://openalex.org/W1507138273","https://openalex.org/W1577692325","https://openalex.org/W1650971489","https://openalex.org/W2008234533","https://openalex.org/W2018148806","https://openalex.org/W2066312471","https://openalex.org/W2068391401","https://openalex.org/W2133640696","https://openalex.org/W2136915956","https://openalex.org/W2146364193","https://openalex.org/W2256962402","https://openalex.org/W2285913470","https://openalex.org/W2317769561","https://openalex.org/W2414372613","https://openalex.org/W3022814278","https://openalex.org/W6637213320","https://openalex.org/W6680227247"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582","https://openalex.org/W2087391438","https://openalex.org/W1966831329","https://openalex.org/W2316074893","https://openalex.org/W2020188645","https://openalex.org/W2049930962"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,12,34,61],"methodology":[4],"for":[5],"recognition":[6,102,126],"of":[7,14,30,103],"plant":[8],"species":[9],"by":[10],"using":[11,60,109],"set":[13],"statistical":[15],"features":[16,24,44],"obtained":[17],"from":[18],"digital":[19],"leaf":[20,32,111],"images.":[21],"As":[22],"the":[23,31,43,77,94,122],"are":[25,54,66,81],"sensitive":[26],"to":[27,41,46,56,85,88,100],"geometric":[28],"transformations":[29,47],"image,":[33],"pre":[35],"processing":[36],"step":[37],"is":[38,97],"initially":[39],"performed":[40],"make":[42],"invariant":[45],"like":[48],"translation,":[49],"rotation":[50],"and":[51,72,83,91,118],"scaling.":[52],"Images":[53],"classified":[55],"32":[57],"pre-defined":[58],"classes":[59],"Neuro":[62],"fuzzy":[63],"classifier.":[64],"Comparisons":[65],"also":[67],"done":[68],"with":[69,105],"Neural":[70],"Network":[71],"k-Nearest":[73],"Neighbor":[74],"classifiers.":[75],"Recognizing":[76],"fact":[78],"that":[79,121],"leaves":[80,104],"fragile":[82],"prone":[84],"deformations":[86,119],"due":[87],"various":[89],"environmental":[90],"biological":[92],"factors,":[93],"basic":[95],"technique":[96,123],"subsequently":[98],"extended":[99],"address":[101],"small":[106],"deformations.":[107],"Experimentations":[108],"640":[110],"images":[112],"varying":[113],"in":[114],"shape,":[115],"size,":[116],"orientations":[117],"demonstrate":[120],"produces":[124],"acceptable":[125],"rates.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
