{"id":"https://openalex.org/W2102749085","doi":"https://doi.org/10.1016/s0925-2312(96)00048-3","title":"Multiscale image segmentation using a hierarchical self-organizing map","display_name":"Multiscale image segmentation using a hierarchical self-organizing map","publication_year":1997,"publication_date":"1997-02-01","ids":{"openalex":"https://openalex.org/W2102749085","doi":"https://doi.org/10.1016/s0925-2312(96)00048-3","mag":"2102749085"},"language":"en","primary_location":{"id":"doi:10.1016/s0925-2312(96)00048-3","is_oa":true,"landing_page_url":"https://doi.org/10.1016/s0925-2312(96)00048-3","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/s0925-2312(96)00048-3","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111655773","display_name":"Suchendra M. Bhandarkar","orcid":null},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Suchendra M. Bhandarkar","raw_affiliation_strings":["Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA","Department of Computer Science , University of Georgia , Athens, GA 30602-7404, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Georgia, Athens, GA 30602-7404, USA","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"Department of Computer Science , University of Georgia , Athens, GA 30602-7404, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111833513","display_name":"Jean Koh","orcid":null},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jean Koh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Syracuse University, Syracuse, NY 13244-1240, USA","Department of Electrical and Computer Engineering Syracuse University Syracuse, NY 13244-1240, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Syracuse University, Syracuse, NY 13244-1240, USA","institution_ids":["https://openalex.org/I70983195"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering Syracuse University Syracuse, NY 13244-1240, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108188128","display_name":"Minsoo Suk","orcid":null},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minsoo Suk","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Syracuse University, Syracuse, NY 13244-1240, USA","Department of Electrical and Computer Engineering Syracuse University Syracuse, NY 13244-1240, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Syracuse University, Syracuse, NY 13244-1240, USA","institution_ids":["https://openalex.org/I70983195"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering Syracuse University Syracuse, NY 13244-1240, USA","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111655773"],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":{"value":2470,"currency":"USD","value_usd":2470},"apc_paid":{"value":2470,"currency":"USD","value_usd":2470},"fwci":4.0953,"has_fulltext":false,"cited_by_count":81,"citation_normalized_percentile":{"value":0.94177598,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"14","issue":"3","first_page":"241","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9846000075340271,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9840999841690063,"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/self-organizing-map","display_name":"Self-organizing map","score":0.806519627571106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7171552181243896},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.7068465352058411},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6796678304672241},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6610257625579834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.649482011795044},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6200099587440491},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.613896369934082},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.6061631441116333},{"id":"https://openalex.org/keywords/minimum-spanning-tree-based-segmentation","display_name":"Minimum spanning tree-based segmentation","score":0.5907943844795227},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.5064245462417603},{"id":"https://openalex.org/keywords/range-segmentation","display_name":"Range segmentation","score":0.4722805917263031},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4629654884338379},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44169512391090393},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4122699499130249},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3699057102203369}],"concepts":[{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.806519627571106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7171552181243896},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.7068465352058411},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6796678304672241},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6610257625579834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.649482011795044},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6200099587440491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.613896369934082},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.6061631441116333},{"id":"https://openalex.org/C42314347","wikidata":"https://www.wikidata.org/wiki/Q6865488","display_name":"Minimum spanning tree-based segmentation","level":5,"score":0.5907943844795227},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.5064245462417603},{"id":"https://openalex.org/C67561299","wikidata":"https://www.wikidata.org/wiki/Q7292710","display_name":"Range segmentation","level":5,"score":0.4722805917263031},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4629654884338379},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44169512391090393},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4122699499130249},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3699057102203369}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/s0925-2312(96)00048-3","is_oa":true,"landing_page_url":"https://doi.org/10.1016/s0925-2312(96)00048-3","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/s0925-2312(96)00048-3","is_oa":true,"landing_page_url":"https://doi.org/10.1016/s0925-2312(96)00048-3","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W21553565","https://openalex.org/W198313105","https://openalex.org/W1590107945","https://openalex.org/W1655554306","https://openalex.org/W1970800786","https://openalex.org/W1972544340","https://openalex.org/W1991848143","https://openalex.org/W1994530392","https://openalex.org/W2030129920","https://openalex.org/W2033849769","https://openalex.org/W2035222930","https://openalex.org/W2046923608","https://openalex.org/W2055350664","https://openalex.org/W2071781501","https://openalex.org/W2073547849","https://openalex.org/W2074429597","https://openalex.org/W2079991241","https://openalex.org/W2080082398","https://openalex.org/W2093413210","https://openalex.org/W2099088762","https://openalex.org/W2109863423","https://openalex.org/W2112272945","https://openalex.org/W2134383396","https://openalex.org/W2141244323","https://openalex.org/W2145023731","https://openalex.org/W2158365276","https://openalex.org/W2160060889","https://openalex.org/W2168487341","https://openalex.org/W2582140298","https://openalex.org/W2740373864","https://openalex.org/W2912717098","https://openalex.org/W2913602408","https://openalex.org/W3100816363","https://openalex.org/W3141386157","https://openalex.org/W4242631611","https://openalex.org/W6608100041","https://openalex.org/W6635434546","https://openalex.org/W6670496014","https://openalex.org/W6676598158","https://openalex.org/W6677336723","https://openalex.org/W6680581086","https://openalex.org/W6732845255","https://openalex.org/W6793421155"],"related_works":["https://openalex.org/W2115198604","https://openalex.org/W2183230975","https://openalex.org/W3185355404","https://openalex.org/W1988767754","https://openalex.org/W2045775567","https://openalex.org/W2566648451","https://openalex.org/W2074857711","https://openalex.org/W2897195263","https://openalex.org/W2102749085","https://openalex.org/W2030415656"],"abstract_inverted_index":{"Multiscale":[0],"structures":[1],"and":[2,10,98,109],"algorithms":[3],"that":[4],"unify":[5],"the":[6,80,101,105,118,121,124,128],"treatment":[7],"of":[8,15,34,79,88,95,107,114,123,130],"local":[9],"global":[11],"scene":[12],"information":[13],"are":[14,56],"particular":[16],"importance":[17],"in":[18,51,127],"image":[19,35,59,67,89,116,131],"segmentation.":[20,36,60,132],"Vector":[21],"quantization,":[22],"owing":[23],"to":[24,29],"its":[25],"versatility,":[26],"has":[27],"proved":[28],"be":[30,41],"an":[31,77],"effective":[32],"means":[33],"Although":[37],"vector":[38,96],"quantization":[39,97],"can":[40],"achieved":[42],"using":[43],"self-organizing":[44,49,63],"maps":[45,50],"with":[46,112],"competitive":[47],"learning,":[48],"their":[52],"original":[53],"single-layer":[54],"structure,":[55],"inadequate":[57],"for":[58,66],"A":[61],"hierarchical":[62],"neural":[64],"network":[65],"segmentation":[68,90,117],"is":[69,76,91],"presented.":[70],"The":[71,86],"Hierarchical":[72],"Self-Organizing":[73,83],"Map":[74,84],"(HSOM)":[75],"extension":[78],"conventional":[81,125],"(single-layer)":[82],"(SOM).":[85],"problem":[87],"formulated":[92],"as":[93],"one":[94],"mapped":[99],"onto":[100],"HSOM.":[102],"By":[103],"combining":[104],"concepts":[106],"self-organization":[108],"topographic":[110],"mapping":[111],"those":[113],"multiscale":[115],"HSOM":[119],"alleviates":[120],"shortcomings":[122],"SOM":[126],"context":[129]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
