{"id":"https://openalex.org/W2108288988","doi":"https://doi.org/10.1109/ijcnn.2009.5178687","title":"Improving the performance of ANN training with an unsupervised filtering method","display_name":"Improving the performance of ANN training with an unsupervised filtering method","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2108288988","doi":"https://doi.org/10.1109/ijcnn.2009.5178687","mag":"2108288988"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://repository.gatech.edu/bitstreams/8cf06a28-f08d-42c5-959c-a9a712984d0a/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089731310","display_name":"Sekou L. Remy","orcid":"https://orcid.org/0000-0003-2332-6890"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sekou Remy","raw_affiliation_strings":["Human-Automation Systems (HumAnS) Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Human-Automation Systems (HumAnS) Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta 30332, USA"],"affiliations":[{"raw_affiliation_string":"Human-Automation Systems (HumAnS) Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Human-Automation Systems (HumAnS) Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005991642","display_name":"Chung Hyuk Park","orcid":"https://orcid.org/0000-0003-0742-6541"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chung Hyuk Park","raw_affiliation_strings":["Human-Automation Systems (HumAnS) Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Human-Automation Systems (HumAnS) Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta 30332, USA"],"affiliations":[{"raw_affiliation_string":"Human-Automation Systems (HumAnS) Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Human-Automation Systems (HumAnS) Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038825611","display_name":"Ayanna Howard","orcid":"https://orcid.org/0000-0003-2609-9371"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayanna M. Howard","raw_affiliation_strings":["Human-Automation Systems (HumAnS) Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Human-Automation Systems (HumAnS) Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta 30332, USA"],"affiliations":[{"raw_affiliation_string":"Human-Automation Systems (HumAnS) Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Human-Automation Systems (HumAnS) Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089731310"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.7698,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7766995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"2627","last_page":"2633"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12072","display_name":"Machine Learning and Algorithms","score":0.9789999723434448,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9778000116348267,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7879632115364075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6665471792221069},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5945510268211365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5944185853004456},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5700172185897827},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5618436336517334},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5611152052879333},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5210651755332947},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5205367803573608},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4947440028190613},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47149819135665894},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11078828573226929},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10530200600624084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08837011456489563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7879632115364075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6665471792221069},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5945510268211365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5944185853004456},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5700172185897827},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5618436336517334},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5611152052879333},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5210651755332947},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5205367803573608},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4947440028190613},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47149819135665894},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11078828573226929},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10530200600624084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08837011456489563},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2009.5178687","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},{"id":"pmh:oai:smartech.gatech.edu:1853/38470","is_oa":true,"landing_page_url":"http://hdl.handle.net/1853/38470","pdf_url":"http://repository.gatech.edu/bitstreams/8cf06a28-f08d-42c5-959c-a9a712984d0a/download","source":{"id":"https://openalex.org/S4377196313","display_name":"SMARTech Repository (Georgia Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I130701444","host_organization_name":"Georgia Institute of Technology","host_organization_lineage":["https://openalex.org/I130701444"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings"}],"best_oa_location":{"id":"pmh:oai:smartech.gatech.edu:1853/38470","is_oa":true,"landing_page_url":"http://hdl.handle.net/1853/38470","pdf_url":"http://repository.gatech.edu/bitstreams/8cf06a28-f08d-42c5-959c-a9a712984d0a/download","source":{"id":"https://openalex.org/S4377196313","display_name":"SMARTech Repository (Georgia Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I130701444","host_organization_name":"Georgia Institute of Technology","host_organization_lineage":["https://openalex.org/I130701444"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6318047389","display_name":"HRI: ROBOT LEARNING FROM TELEOPERATIVE-BASED INSTRUCTION AND MULTIMODAL INTERACTION","funder_award_id":"0705130","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6825202671","display_name":null,"funder_award_id":"IIS-0705130","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2108288988.pdf","grobid_xml":"https://content.openalex.org/works/W2108288988.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1584762295","https://openalex.org/W1708197474","https://openalex.org/W2073768640","https://openalex.org/W2104352549","https://openalex.org/W2104876183","https://openalex.org/W2108259386","https://openalex.org/W2109302642","https://openalex.org/W2119388568","https://openalex.org/W2125769353","https://openalex.org/W2140481308","https://openalex.org/W2142592520","https://openalex.org/W2142616273","https://openalex.org/W2166302491","https://openalex.org/W2539005893","https://openalex.org/W2539485310","https://openalex.org/W2970576388"],"related_works":["https://openalex.org/W3161249280","https://openalex.org/W2267059662","https://openalex.org/W2364268683","https://openalex.org/W4388411807","https://openalex.org/W1519906715","https://openalex.org/W2478803962","https://openalex.org/W3169430512","https://openalex.org/W2384804534","https://openalex.org/W2154069781","https://openalex.org/W3098003361"],"abstract_inverted_index":{"Learning":[0],"control":[1],"strategies":[2],"from":[3],"examples":[4],"has":[5],"been":[6],"identified":[7],"as":[8,99],"an":[9],"important":[10],"capability":[11],"for":[12,47],"many":[13],"robotic":[14],"systems.":[15],"In":[16,87],"this":[17],"work":[18],"we":[19],"show":[20,53],"how":[21],"the":[22,31,40,50,54,70,76,88,91,96,100,103],"learning":[23,41],"process":[24],"can":[25],"be":[26,110],"aided":[27],"by":[28],"autonomously":[29],"filtering":[30,59],"training":[32,77],"set":[33],"provided":[34],"to":[35,74,83,109],"improve":[36],"key":[37],"properties":[38],"of":[39,69,117],"process.":[42],"Demonstrated":[43],"with":[44,65],"data":[45],"gathered":[46],"manipulation":[48],"tasks,":[49],"results":[51],"herein":[52],"improved":[55],"performance":[56],"when":[57],"autonomous":[58],"is":[60],"applied.":[61],"The":[62],"filtration":[63],"method,":[64],"no":[66],"prior":[67],"knowledge":[68],"task,":[71],"was":[72],"able":[73],"partition":[75],"sets":[78,80],"into":[79],"almost":[81],"equal":[82],"expertly":[84],"labeled":[85],"sets.":[86],"case":[89],"where":[90],"filter":[92],"did":[93],"not":[94],"produce":[95],"same":[97],"groupings":[98],"expert":[101],"user,":[102],"method":[104],"still":[105],"permitted":[106],"a":[107,114],"controller":[108],"trained":[111],"which":[112],"demonstrated":[113],"success":[115],"rate":[116],"92%.":[118]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
