{"id":"https://openalex.org/W2083561184","doi":"https://doi.org/10.1109/siu.2014.6830674","title":"Plant identification using local invariants","display_name":"Plant identification using local invariants","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W2083561184","doi":"https://doi.org/10.1109/siu.2014.6830674","mag":"2083561184"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2014.6830674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2014.6830674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","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/A5087512984","display_name":"S. Tolga Yildiran","orcid":null},"institutions":[{"id":"https://openalex.org/I134235054","display_name":"Sabanc\u0131 \u00dcniversitesi","ror":"https://ror.org/049asqa32","country_code":"TR","type":"education","lineage":["https://openalex.org/I134235054"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"S. Tolga Yildiran","raw_affiliation_strings":["[M\u00fchendislik ve Do\u011fa Bilimleri Fak\u00fcltesi Sabanc\u0131 \u00dcniversitesi]"],"affiliations":[{"raw_affiliation_string":"[M\u00fchendislik ve Do\u011fa Bilimleri Fak\u00fcltesi Sabanc\u0131 \u00dcniversitesi]","institution_ids":["https://openalex.org/I134235054"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057031258","display_name":"Berrin Yan\u0131ko\u011flu","orcid":"https://orcid.org/0000-0001-7403-7592"},"institutions":[{"id":"https://openalex.org/I134235054","display_name":"Sabanc\u0131 \u00dcniversitesi","ror":"https://ror.org/049asqa32","country_code":"TR","type":"education","lineage":["https://openalex.org/I134235054"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Benin Yanikoglu","raw_affiliation_strings":["[M\u00fchendislik ve Do\u011fa Bilimleri Fak\u00fcltesi Sabanc\u0131 \u00dcniversitesi]"],"affiliations":[{"raw_affiliation_string":"[M\u00fchendislik ve Do\u011fa Bilimleri Fak\u00fcltesi Sabanc\u0131 \u00dcniversitesi]","institution_ids":["https://openalex.org/I134235054"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086498001","display_name":"Erhan Abdullah","orcid":null},"institutions":[{"id":"https://openalex.org/I96268669","display_name":"Okan University","ror":"https://ror.org/054d5vq03","country_code":"TR","type":"education","lineage":["https://openalex.org/I96268669"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Erhan Abdullah","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Okan \u00dcniversitesi"],"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Okan \u00dcniversitesi","institution_ids":["https://openalex.org/I96268669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087512984"],"corresponding_institution_ids":["https://openalex.org/I134235054"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.14367977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2094","last_page":"2097"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9955000281333923,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.8548272848129272},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7024136185646057},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7017519474029541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6980264186859131},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6621987223625183},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5578224658966064},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5265942811965942},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5160465240478516},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48262080550193787},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.482557475566864},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41644829511642456},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.3251550793647766},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3219679892063141},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3212538957595825},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.2837015390396118},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.06586688756942749}],"concepts":[{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.8548272848129272},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7024136185646057},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7017519474029541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6980264186859131},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6621987223625183},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5578224658966064},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5265942811965942},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5160465240478516},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48262080550193787},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.482557475566864},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41644829511642456},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.3251550793647766},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3219679892063141},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3212538957595825},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2837015390396118},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.06586688756942749},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2014.6830674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2014.6830674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","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":10,"referenced_works":["https://openalex.org/W1230023165","https://openalex.org/W2111993661","https://openalex.org/W2148596671","https://openalex.org/W2150856297","https://openalex.org/W2151103935","https://openalex.org/W2162915993","https://openalex.org/W2533598788","https://openalex.org/W4239510810","https://openalex.org/W4252840825","https://openalex.org/W6628174443"],"related_works":["https://openalex.org/W2049930962","https://openalex.org/W2158102958","https://openalex.org/W2086564093","https://openalex.org/W1995462736","https://openalex.org/W2028757524","https://openalex.org/W2548286644","https://openalex.org/W2009049007","https://openalex.org/W2588241640","https://openalex.org/W2045213079","https://openalex.org/W2938717424"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,39,57],"plant":[3],"image":[4],"recognition":[5],"system":[6,13],"geared":[7],"towards":[8],"plants":[9],"with":[10,17],"flowers.":[11],"The":[12],"uses":[14],"local":[15],"invariants":[16],"Dense":[18],"SIFT":[19],"features":[20],"and":[21],"Bag":[22],"of":[23,53,60],"Visual":[24],"Words":[25],"representation,":[26],"while":[27],"the":[28,51,54,61,65,76],"classification":[29,66],"is":[30,68],"done":[31],"using":[32],"Support":[33],"Vector":[34],"Machines.":[35],"Our":[36],"approach":[37],"contains":[38],"pre-classification":[40],"stage":[41],"where":[42],"images":[43],"are":[44],"categorized":[45],"into":[46],"color":[47],"subgroups,":[48],"to":[49,73],"reduce":[50],"complexity":[52],"problem.":[55],"Using":[56],"161-class":[58],"subset":[59],"ImageClef'2013":[62],"flower":[63],"dataset,":[64],"accuracy":[67],"measured":[69],"as":[70],"%42.68,":[71],"compared":[72],"%18":[74],"eithout":[75],"pre-classification.":[77]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
