{"id":"https://openalex.org/W3000618505","doi":"https://doi.org/10.1109/ivcnz48456.2019.8961023","title":"Coniferous Trees Needles-Based Taxonomy Classification","display_name":"Coniferous Trees Needles-Based Taxonomy Classification","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3000618505","doi":"https://doi.org/10.1109/ivcnz48456.2019.8961023","mag":"3000618505"},"language":"en","primary_location":{"id":"doi:10.1109/ivcnz48456.2019.8961023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz48456.2019.8961023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Image and Vision Computing New Zealand (IVCNZ)","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/A5044207475","display_name":"Michal Haindl","orcid":"https://orcid.org/0000-0001-8159-3685"},"institutions":[{"id":"https://openalex.org/I4210119419","display_name":"Czech Academy of Sciences, Institute of Information Theory and Automation","ror":"https://ror.org/03h1hsz49","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210119419"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Michal Haindl","raw_affiliation_strings":["The Institute of Information Theory and Automation of the Czech Academy of Sciences,Pattern Recognition Dep.,Prague,Czechia","Pattern Recognition Dep., The Institute of Information Theory and Automation of the Czech Academy of Sciences, Prague, Czechia"],"affiliations":[{"raw_affiliation_string":"The Institute of Information Theory and Automation of the Czech Academy of Sciences,Pattern Recognition Dep.,Prague,Czechia","institution_ids":["https://openalex.org/I4210119419"]},{"raw_affiliation_string":"Pattern Recognition Dep., The Institute of Information Theory and Automation of the Czech Academy of Sciences, Prague, Czechia","institution_ids":["https://openalex.org/I4210119419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036783774","display_name":"Pavel \u017did","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119419","display_name":"Czech Academy of Sciences, Institute of Information Theory and Automation","ror":"https://ror.org/03h1hsz49","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210119419"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Pavel \u017did","raw_affiliation_strings":["The Institute of Information Theory and Automation of the Czech Academy of Sciences,Pattern Recognition Dep.,Prague,Czechia","Pattern Recognition Dep., The Institute of Information Theory and Automation of the Czech Academy of Sciences, Prague, Czechia"],"affiliations":[{"raw_affiliation_string":"The Institute of Information Theory and Automation of the Czech Academy of Sciences,Pattern Recognition Dep.,Prague,Czechia","institution_ids":["https://openalex.org/I4210119419"]},{"raw_affiliation_string":"Pattern Recognition Dep., The Institute of Information Theory and Automation of the Czech Academy of Sciences, Prague, Czechia","institution_ids":["https://openalex.org/I4210119419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044207475"],"corresponding_institution_ids":["https://openalex.org/I4210119419"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16674653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9768999814987183,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9768999814987183,"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/T13568","display_name":"Wood and Agarwood Research","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9623000025749207,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8073017597198486},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7865160703659058},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7046754360198975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6932728290557861},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6777775287628174},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.6104766130447388},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.541566789150238},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5177747011184692},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3431985676288605},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.18278026580810547},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14386004209518433}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8073017597198486},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7865160703659058},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7046754360198975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6932728290557861},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6777775287628174},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.6104766130447388},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.541566789150238},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5177747011184692},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3431985676288605},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.18278026580810547},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14386004209518433}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivcnz48456.2019.8961023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz48456.2019.8961023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Image and Vision Computing New Zealand (IVCNZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W10646069","https://openalex.org/W2009958428","https://openalex.org/W2104332083","https://openalex.org/W2116132882","https://openalex.org/W2293174486","https://openalex.org/W2568155635","https://openalex.org/W2887434521","https://openalex.org/W2954848990"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W2165912799","https://openalex.org/W4388409104","https://openalex.org/W2965546495","https://openalex.org/W1487808658","https://openalex.org/W2761785940","https://openalex.org/W2129933262","https://openalex.org/W2005234362","https://openalex.org/W1997235926"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"multispectral":[3,28,58],"rotationally":[4,60],"in-variant":[5],"textural":[6,44],"features":[7,22],"of":[8,49],"the":[9,14,26,34,50,86],"Markovian":[10],"type":[11],"applied":[12],"for":[13,67,75],"effective":[15],"coniferous":[16,77,100],"tree":[17,78,101],"needles":[18,51,68,89],"categorization.":[19],"Presented":[20],"texture":[21,36,52],"are":[23],"inferred":[24],"from":[25,97],"descriptive":[27,57],"spiral":[29],"wide-sense":[30],"Markov":[31],"model.":[32],"Unlike":[33],"alternative":[35],"recognition":[37],"methods":[38],"based":[39],"on":[40,85],"various":[41],"gray-scale":[42],"discriminative":[43],"descriptions,":[45],"we":[46],"take":[47],"advantage":[48],"representation,":[53],"which":[54,92],"is":[55,83],"fully":[56],"and":[59],"invariant.The":[61],"presented":[62],"method":[63],"achieves":[64],"high":[65],"accuracy":[66],"recognition.":[69],"Thus":[70],"it":[71],"can":[72],"be":[73],"used":[74],"reliable":[76],"taxon":[79],"classification.":[80],"Our":[81],"classifier":[82],"tested":[84],"open":[87],"source":[88],"database":[90],"Aff,":[91],"contains":[93],"716":[94],"high-resolution":[95],"images":[96],"11":[98],"diverse":[99],"species.":[102]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
