{"id":"https://openalex.org/W4313495773","doi":"https://doi.org/10.1109/scisisis55246.2022.10001909","title":"A method for estimating the volume of clusters built by Growing Neural Gas","display_name":"A method for estimating the volume of clusters built by Growing Neural Gas","publication_year":2022,"publication_date":"2022-11-29","ids":{"openalex":"https://openalex.org/W4313495773","doi":"https://doi.org/10.1109/scisisis55246.2022.10001909"},"language":"en","primary_location":{"id":"doi:10.1109/scisisis55246.2022.10001909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/scisisis55246.2022.10001909","pdf_url":null,"source":{"id":"https://openalex.org/S4363607982","display_name":"2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&amp;ISIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&amp;ISIS)","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/A5100350230","display_name":"Qi Li","orcid":"https://orcid.org/0000-0002-7214-8122"},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["Okayama University,Graduate School of Natural Science and Technology,Okayama,Japan","Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Okayama University,Graduate School of Natural Science and Technology,Okayama,Japan","institution_ids":["https://openalex.org/I163770644"]},{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087750601","display_name":"Yuichiro Toda","orcid":"https://orcid.org/0000-0003-4170-2300"},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuichiro Toda","raw_affiliation_strings":["Okayama University,Graduate School of Natural Science and Technology,Okayama,Japan","Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Okayama University,Graduate School of Natural Science and Technology,Okayama,Japan","institution_ids":["https://openalex.org/I163770644"]},{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091376701","display_name":"Takayuki Matsuno","orcid":"https://orcid.org/0000-0003-3372-0912"},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Matsuno","raw_affiliation_strings":["Okayama University,Graduate School of Natural Science and Technology,Okayama,Japan","Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Okayama University,Graduate School of Natural Science and Technology,Okayama,Japan","institution_ids":["https://openalex.org/I163770644"]},{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan","institution_ids":["https://openalex.org/I163770644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.059,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.33967488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9757000207901001,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9757000207901001,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9692999720573425,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9610999822616577,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/neural-gas","display_name":"Neural gas","score":0.8807937502861023},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8108716011047363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7408140897750854},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7032838463783264},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.6398277282714844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6029208302497864},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5760429501533508},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5027692317962646},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4697687327861786},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44985827803611755},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41752728819847107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3860304057598114},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3426400423049927},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.21438688039779663},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11947381496429443},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07194575667381287}],"concepts":[{"id":"https://openalex.org/C90322556","wikidata":"https://www.wikidata.org/wiki/Q1981169","display_name":"Neural gas","level":4,"score":0.8807937502861023},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8108716011047363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7408140897750854},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7032838463783264},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6398277282714844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6029208302497864},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5760429501533508},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5027692317962646},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4697687327861786},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44985827803611755},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41752728819847107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3860304057598114},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3426400423049927},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.21438688039779663},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11947381496429443},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07194575667381287},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/scisisis55246.2022.10001909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/scisisis55246.2022.10001909","pdf_url":null,"source":{"id":"https://openalex.org/S4363607982","display_name":"2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&amp;ISIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&amp;ISIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1503652263","https://openalex.org/W1970387420","https://openalex.org/W2027946968","https://openalex.org/W2065824652","https://openalex.org/W2089468765","https://openalex.org/W2138754805","https://openalex.org/W2341115255","https://openalex.org/W2560973310","https://openalex.org/W2790538633","https://openalex.org/W2882985702","https://openalex.org/W2921967421","https://openalex.org/W2963719584","https://openalex.org/W4210904135","https://openalex.org/W6637308636","https://openalex.org/W6680294583"],"related_works":["https://openalex.org/W4389574804","https://openalex.org/W3016928466","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W3108295644","https://openalex.org/W1578717197","https://openalex.org/W2626737336","https://openalex.org/W2005998065","https://openalex.org/W4298130764","https://openalex.org/W4282934273"],"abstract_inverted_index":{"3D":[0,25,84],"space":[1],"perception":[2],"is":[3],"playing":[4],"an":[5],"important":[6],"role":[7],"in":[8,15],"autonomous":[9],"robots":[10],"completing":[11],"a":[12,33,54,61,70],"task":[13],"adaptively":[14],"the":[16,24,76,90],"form":[17],"of":[18,27,72,75],"detecting":[19],"target":[20,28],"objects":[21],"and":[22,83,93],"estimating":[23],"pose":[26],"objects.":[29],"This":[30],"paper":[31],"utilizes":[32],"growing":[34],"neural":[35],"gas":[36],"(GNG)":[37],"based":[38,63],"method":[39,78,92],"called":[40],"GNG":[41,62],"with":[42],"different":[43],"topologies":[44],"(GNG-DT)":[45],"for":[46,52],"reconstructing":[47],"unstructured":[48],"point":[49,85],"clouds.":[50],"Next,":[51],"extracting":[53],"feature":[55],"from":[56],"clustering":[57],"results,":[58],"we":[59,68],"propose":[60],"volume":[64],"estimation":[65],"method.":[66],"Finally,":[67],"display":[69],"sequence":[71],"experimental":[73],"results":[74],"proposed":[77,91],"using":[79],"simulation":[80],"data":[81],"sets":[82],"cloud":[86],"datasets":[87],"to":[88],"evaluate":[89],"discuss":[94],"its":[95],"effectiveness.":[96]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
