{"id":"https://openalex.org/W2029348842","doi":"https://doi.org/10.1109/ijcnn.2013.6706825","title":"Feature extraction based on hierarchical growing neural gas for informationally structured space","display_name":"Feature extraction based on hierarchical growing neural gas for informationally structured space","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2029348842","doi":"https://doi.org/10.1109/ijcnn.2013.6706825","mag":"2029348842"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2013.6706825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6706825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","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/A5087750601","display_name":"Yuichiro Toda","orcid":"https://orcid.org/0000-0003-4170-2300"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuichiro Toda","raw_affiliation_strings":["Tokyo Metropolitan University, Tokyo, Japan","Tokyo Metropolitan University, Hino, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]},{"raw_affiliation_string":"Tokyo Metropolitan University, Hino, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074076109","display_name":"Naoyuki Kubota","orcid":"https://orcid.org/0000-0001-8829-037X"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoyuki Kubota","raw_affiliation_strings":["Tokyo Metropolitan University, Tokyo, Japan","Tokyo Metropolitan University, Hino, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]},{"raw_affiliation_string":"Tokyo Metropolitan University, Hino, Japan","institution_ids":["https://openalex.org/I69740276"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087750601"],"corresponding_institution_ids":["https://openalex.org/I69740276"],"apc_list":null,"apc_paid":null,"fwci":0.8662,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.81040284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9919000267982483,"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/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/computer-science","display_name":"Computer science","score":0.7499097585678101},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7005473971366882},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6811429262161255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6368303298950195},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6287268996238708},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6162621974945068},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5638264417648315},{"id":"https://openalex.org/keywords/neural-gas","display_name":"Neural gas","score":0.5352839231491089},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5213914513587952},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4744476079940796},{"id":"https://openalex.org/keywords/virtual-space","display_name":"Virtual space","score":0.4301793873310089},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4209015369415283},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3858010172843933},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35184526443481445},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.14049243927001953},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08531290292739868}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7499097585678101},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7005473971366882},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6811429262161255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6368303298950195},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6287268996238708},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6162621974945068},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5638264417648315},{"id":"https://openalex.org/C90322556","wikidata":"https://www.wikidata.org/wiki/Q1981169","display_name":"Neural gas","level":4,"score":0.5352839231491089},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5213914513587952},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4744476079940796},{"id":"https://openalex.org/C2985021205","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual space","level":2,"score":0.4301793873310089},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4209015369415283},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3858010172843933},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35184526443481445},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.14049243927001953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08531290292739868},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2013.6706825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6706825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","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":25,"referenced_works":["https://openalex.org/W1543136774","https://openalex.org/W1677409904","https://openalex.org/W1972671602","https://openalex.org/W1984860818","https://openalex.org/W1993267444","https://openalex.org/W2000018820","https://openalex.org/W2000296245","https://openalex.org/W2010150441","https://openalex.org/W2024668293","https://openalex.org/W2027946968","https://openalex.org/W2072723786","https://openalex.org/W2083868427","https://openalex.org/W2108449247","https://openalex.org/W2119851068","https://openalex.org/W2132888444","https://openalex.org/W2138754805","https://openalex.org/W2144594079","https://openalex.org/W2150397121","https://openalex.org/W2166798375","https://openalex.org/W2399775579","https://openalex.org/W6632430232","https://openalex.org/W6637400245","https://openalex.org/W6680294583","https://openalex.org/W6682291664","https://openalex.org/W6684808992"],"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/W2536637991","https://openalex.org/W2358780699","https://openalex.org/W2131324717","https://openalex.org/W1533929815"],"abstract_inverted_index":{"This":[0,61],"paper":[1],"proposes":[2],"a":[3],"method":[4,52,62,79,94,99,111],"of":[5,36,65,95,108,116],"feature":[6,97],"extraction":[7],"from":[8],"3D":[9,76,87],"point":[10,88],"clouds":[11],"for":[12,22,41],"informationally":[13,27],"structured":[14,28],"space":[15,29],"including":[16],"sensor":[17],"networks":[18],"and":[19,34,38,44,48,112],"robot":[20],"partners":[21],"co-existing":[23],"with":[24],"people.":[25],"The":[26],"realizes":[30],"the":[31,86,93,96,109,114,117],"quick":[32],"update":[33],"access":[35],"valuable":[37],"useful":[39],"information":[40],"both":[42],"people":[43],"robots":[45],"on":[46,55,70,101],"real":[47],"virtual":[49],"environments.":[50],"Our":[51],"is":[53,63],"based":[54,69,100],"Hierarchical":[56],"Growing":[57],"Neural":[58],"Gas":[59],"(HGNG).":[60],"one":[64],"self-organizing":[66],"neural":[67],"network":[68],"unsupervised":[71],"learning":[72],"First,":[73],"we":[74,91,104],"propose":[75,92],"map":[77],"building":[78],"using":[80],"Kinect":[81],"in":[82],"order":[83],"to":[84],"acquire":[85],"clouds.":[89],"Next,":[90],"extracting":[98],"HGNG.":[102],"Finally,":[103],"show":[105],"experimental":[106],"results":[107],"proposed":[110,118],"discuss":[113],"effectiveness":[115],"method.":[119]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
