{"id":"https://openalex.org/W2002033532","doi":"https://doi.org/10.1109/ijcnn.2012.6252764","title":"Region analysis through close contour transformation using growing neural gas","display_name":"Region analysis through close contour transformation using growing neural gas","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2002033532","doi":"https://doi.org/10.1109/ijcnn.2012.6252764","mag":"2002033532"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2012.6252764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5081778658","display_name":"Gaurav Gupta","orcid":"https://orcid.org/0000-0001-7763-3090"},"institutions":[{"id":"https://openalex.org/I94951947","display_name":"University of Westminster","ror":"https://ror.org/04ycpbx82","country_code":"GB","type":"education","lineage":["https://openalex.org/I94951947"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gaurav Gupta","raw_affiliation_strings":["School of Electronics and Computer Science, University of Westminster, London, UK","[School of Electronics and Computer Science, University of Westminster, London, UK]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Westminster, London, UK","institution_ids":["https://openalex.org/I94951947"]},{"raw_affiliation_string":"[School of Electronics and Computer Science, University of Westminster, London, UK]","institution_ids":["https://openalex.org/I94951947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063682950","display_name":"\u0391\u03bb\u03b5\u03be\u03ac\u03bd\u03b4\u03c1\u03b1 \u03a8\u03b1\u03c1\u03c1\u03bf\u03cd","orcid":"https://orcid.org/0000-0003-3167-3454"},"institutions":[{"id":"https://openalex.org/I94951947","display_name":"University of Westminster","ror":"https://ror.org/04ycpbx82","country_code":"GB","type":"education","lineage":["https://openalex.org/I94951947"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alexandra Psarrou","raw_affiliation_strings":["School of Electronics and Computer Science, University of Westminster, London, UK","[School of Electronics and Computer Science, University of Westminster, London, UK]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Westminster, London, UK","institution_ids":["https://openalex.org/I94951947"]},{"raw_affiliation_string":"[School of Electronics and Computer Science, University of Westminster, London, UK]","institution_ids":["https://openalex.org/I94951947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086573631","display_name":"Anastassia Angelopoulou","orcid":"https://orcid.org/0000-0003-1453-492X"},"institutions":[{"id":"https://openalex.org/I94951947","display_name":"University of Westminster","ror":"https://ror.org/04ycpbx82","country_code":"GB","type":"education","lineage":["https://openalex.org/I94951947"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Anastasia Angelopoulou","raw_affiliation_strings":["School of Electronics and Computer Science, University of Westminster, London, UK","[School of Electronics and Computer Science, University of Westminster, London, UK]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Westminster, London, UK","institution_ids":["https://openalex.org/I94951947"]},{"raw_affiliation_string":"[School of Electronics and Computer Science, University of Westminster, London, UK]","institution_ids":["https://openalex.org/I94951947"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079599826","display_name":"Jos\u00e9 Garc\u00eda\u2010Rodr\u00edguez","orcid":"https://orcid.org/0000-0002-7798-3055"},"institutions":[{"id":"https://openalex.org/I130194489","display_name":"University of Alicante","ror":"https://ror.org/05t8bcz72","country_code":"ES","type":"education","lineage":["https://openalex.org/I130194489"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jose Garcia-Rodriguez","raw_affiliation_strings":["Department of Computing Technology, University of Alicante, Spain","Department of Computing Technology, University of Alicante, Spain#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computing Technology, University of Alicante, Spain","institution_ids":["https://openalex.org/I130194489"]},{"raw_affiliation_string":"Department of Computing Technology, University of Alicante, Spain#TAB#","institution_ids":["https://openalex.org/I130194489"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9958999752998352,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9882000088691711,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7293345928192139},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7120611071586609},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7006288170814514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6587607860565186},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5981166362762451},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5822033882141113},{"id":"https://openalex.org/keywords/neural-gas","display_name":"Neural gas","score":0.5579509139060974},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5390791893005371},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.538711428642273},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5063349008560181},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4893157184123993},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4531266689300537},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44863009452819824},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2825939357280731},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20047405362129211},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.18011200428009033},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08522093296051025}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7293345928192139},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7120611071586609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7006288170814514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6587607860565186},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5981166362762451},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5822033882141113},{"id":"https://openalex.org/C90322556","wikidata":"https://www.wikidata.org/wiki/Q1981169","display_name":"Neural gas","level":4,"score":0.5579509139060974},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5390791893005371},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.538711428642273},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5063349008560181},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4893157184123993},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4531266689300537},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44863009452819824},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2825939357280731},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20047405362129211},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.18011200428009033},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08522093296051025},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2012.6252764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:westminsterresearch.westminster.ac.uk:8z7qw","is_oa":false,"landing_page_url":"https://doi.org/10.1109/IJCNN.2012.6252764","pdf_url":null,"source":{"id":"https://openalex.org/S4306400277","display_name":"WestminsterResearch (University of Westminster)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I94951947","host_organization_name":"University of Westminster","host_organization_lineage":["https://openalex.org/I94951947"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7699999809265137,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W191001584","https://openalex.org/W1569765338","https://openalex.org/W1765494715","https://openalex.org/W1978613449","https://openalex.org/W1985372187","https://openalex.org/W2042584910","https://openalex.org/W2046150577","https://openalex.org/W2061469806","https://openalex.org/W2098689350","https://openalex.org/W2100318434","https://openalex.org/W2108556791","https://openalex.org/W2113530345","https://openalex.org/W2115940483","https://openalex.org/W2122854906","https://openalex.org/W2123815996","https://openalex.org/W2138754805","https://openalex.org/W2146168286","https://openalex.org/W2154332114","https://openalex.org/W2177690825","https://openalex.org/W2480035597","https://openalex.org/W2574358302","https://openalex.org/W4245176872","https://openalex.org/W6680294583","https://openalex.org/W6732235260"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374"],"abstract_inverted_index":{"In":[0],"our":[1],"work":[2],"we":[3],"aim":[4],"to":[5,48,55,64,77,110],"explore":[6],"a":[7,30,36,57,95,101,139],"general":[8],"framework":[9],"that":[10,105],"addresses":[11],"the":[12,39,69,107,115,125,144,150],"fundamental":[13],"problem":[14],"of":[15,19,117,127,146],"universal":[16],"unsupervised":[17],"extraction":[18],"semantically":[20],"meaningful":[21],"visual":[22],"regions.":[23],"To":[24],"this":[25,27],"end":[26],"paper":[28],"describes":[29],"novel":[31],"region":[32,62,92],"analysis":[33],"technique":[34],"using":[35],"self-organising":[37],"map,":[38],"growing":[40,70],"neural":[41,71],"gas,":[42],"which":[43],"is":[44,103],"adapted":[45],"so":[46],"as":[47,52,54],"improve":[49],"modelling":[50],"speed":[51],"well":[53],"ensure":[56],"double-linkage":[58],"chain":[59],"around":[60],"all":[61],"contours":[63,130,134],"simplify":[65],"shape":[66,78],"analysis.":[67],"While":[68],"gas":[72],"has":[73,81,98],"been":[74,84,99],"extensively":[75],"applied":[76,104],"modelling,":[79],"it":[80],"never":[82],"explicitly":[83],"used":[85,142],"for":[86,143],"curvature":[87],"analysis,":[88],"contour":[89,96,109,153],"description":[90],"and":[91,131,137,152],"similarity.":[93],"Once":[94],"network":[97],"obtained,":[100],"transformation":[102],"converts":[106],"closed":[108],"an":[111],"open":[112],"one,":[113],"facilitating":[114],"use":[116],"certain":[118],"angular":[119],"descriptors.":[120],"Discriminative":[121],"descriptors":[122],"derived":[123],"from":[124],"properties":[126],"regions,":[128],"their":[129,132],"transformed":[133],"are":[135],"established":[136],"define":[138],"feature":[140],"vector":[141],"representation":[145],"regions":[147],"based":[148],"on":[149],"appearance":[151],"information.":[154]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}