{"id":"https://openalex.org/W4312536459","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892143","title":"Less is more: Low-precision feature selection for wearables","display_name":"Less is more: Low-precision feature selection for wearables","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312536459","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892143"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892143","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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 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/A5035626927","display_name":"Samuel Su\u00e1rez\u2010Marcote","orcid":"https://orcid.org/0009-0004-0228-2678"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel Suarez-Marcote","raw_affiliation_strings":["Universidade da Coruña,CITIC,Department of Computer Science and Information Technologies,A Coruña,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade da Coruña,CITIC,Department of Computer Science and Information Technologies,A Coruña,Spain","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040892787","display_name":"Laura Moran-Femandez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laura Moran-Femandez","raw_affiliation_strings":["Universidade da Coruña,CITIC,Department of Computer Science and Information Technologies,A Coruña,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade da Coruña,CITIC,Department of Computer Science and Information Technologies,A Coruña,Spain","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042436168","display_name":"Ver\u00f3nica Bol\u00f3n\u2010Canedo","orcid":"https://orcid.org/0000-0002-0524-6427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Veronica Bolon-Canedo","raw_affiliation_strings":["Universidade da Coruña,CITIC,Department of Computer Science and Information Technologies,A Coruña,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade da Coruña,CITIC,Department of Computer Science and Information Technologies,A Coruña,Spain","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3114,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52621256,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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/T10320","display_name":"Neural Networks and Applications","score":0.9927999973297119,"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/T10057","display_name":"Face and Expression Recognition","score":0.9902999997138977,"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/computer-science","display_name":"Computer science","score":0.7635713815689087},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6376211047172546},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6100501418113708},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5787457823753357},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5728833079338074},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5619339942932129},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5471405982971191},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.543222963809967},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5430116653442383},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5185223817825317},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4957335889339447},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.47166335582733154},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44840362668037415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4378037750720978},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.42757201194763184},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4274854063987732},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4139101803302765},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37095391750335693},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3081674575805664},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13366535305976868}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7635713815689087},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6376211047172546},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6100501418113708},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5787457823753357},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5728833079338074},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5619339942932129},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5471405982971191},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.543222963809967},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5430116653442383},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5185223817825317},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4957335889339447},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.47166335582733154},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44840362668037415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4378037750720978},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.42757201194763184},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4274854063987732},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4139101803302765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37095391750335693},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3081674575805664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13366535305976868},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892143","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:ruc.udc.es:2183/40204","is_oa":false,"landing_page_url":"http://hdl.handle.net/2183/40204","pdf_url":null,"source":{"id":"https://openalex.org/S4306402204","display_name":"RUC (Universidade Da Coru\u00f1a)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1553145417","https://openalex.org/W1565746575","https://openalex.org/W1841592590","https://openalex.org/W1922017469","https://openalex.org/W1999085092","https://openalex.org/W2016944307","https://openalex.org/W2040884411","https://openalex.org/W2043772506","https://openalex.org/W2087025987","https://openalex.org/W2099111195","https://openalex.org/W2114771311","https://openalex.org/W2119387367","https://openalex.org/W2154053567","https://openalex.org/W2155344811","https://openalex.org/W2156504490","https://openalex.org/W2286365479","https://openalex.org/W2337344472","https://openalex.org/W2416799949","https://openalex.org/W2524428287","https://openalex.org/W2907970550","https://openalex.org/W2962788286","https://openalex.org/W2963122961","https://openalex.org/W2966086598","https://openalex.org/W2970601456","https://openalex.org/W3101100041","https://openalex.org/W4237171445","https://openalex.org/W4244238212","https://openalex.org/W4246834959","https://openalex.org/W6633774736","https://openalex.org/W6638783484","https://openalex.org/W6661428214","https://openalex.org/W6682686508","https://openalex.org/W6683024897","https://openalex.org/W6696004547","https://openalex.org/W6727208969","https://openalex.org/W6767298317","https://openalex.org/W6785662278"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W4391160746","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3090300519","https://openalex.org/W3089231081"],"abstract_inverted_index":{"Nowadays,":[0],"the":[1,12,15,27,40,48,56,71,89,125,148,169,174],"amount":[2],"of":[3,17,29,42,50,58,88,127],"data":[4,73],"produced":[5],"daily":[6],"has":[7],"significantly":[8],"increased":[9],"due":[10,38],"to":[11,39,68,111,134,141,162,168],"growth":[13],"in":[14,26,55,95,144,157,177],"number":[16],"wearable":[18],"devices.":[19,44],"Similarly,":[20],"this":[21,96],"increase":[22],"is":[23,65],"also":[24],"visible":[25],"interest":[28],"developing":[30],"machine":[31],"learning":[32],"algorithms":[33],"with":[34,70,138,151],"reduced":[35],"precision":[36,53,101],"computations,":[37],"limitations":[41],"such":[43],"This":[45,75],"work":[46],"studies":[47],"effect":[49],"using":[51,173],"low":[52,100],"operations":[54],"context":[57],"feature":[59,80,136],"selection,":[60],"a":[61],"preprocessing":[62],"step":[63],"that":[64,124],"becoming":[66],"necessary":[67],"deal":[69],"increasing":[72],"dimensionality.":[74],"study":[76],"focuses":[77],"specifically":[78],"on":[79,84],"selection":[81],"methods":[82],"based":[83],"Mutual":[85],"Information":[86],"(one":[87],"most":[90],"popular":[91],"and":[92,98,119,154],"widely-used":[93],"metrics":[94],"area)":[97],"how":[99],"computations":[102],"can":[103],"be":[104],"carried":[105],"out":[106],"obtaining":[107],"experimental":[108],"results":[109],"similar":[110,163],"those":[112,142],"achieved":[113],"by":[114],"double-precision":[115],"over":[116],"several":[117],"low-":[118],"high-dimensional":[120],"datasets.":[121],"We":[122],"observe":[123],"use":[126],"16-bit":[128],"fixed-point":[129],"representation":[130,176],"makes":[131],"it":[132],"possible":[133],"obtain":[135],"rankings":[137,149],"high":[139],"similarity":[140],"obtained":[143,150,171],"double-":[145],"precision.":[146],"Even":[147],"8":[152],"bits":[153],"then":[155],"used":[156],"subsequent":[158],"classification":[159],"tasks,":[160],"lead":[161],"accuracy":[164],"(no":[165],"significant":[166],"difference)":[167],"one":[170],"when":[172],"64-bit":[175],"certain":[178],"situations.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}