{"id":"https://openalex.org/W2913598954","doi":"https://doi.org/10.1109/icecs.2018.8617900","title":"Tunable Floating-Point for Artificial Neural Networks","display_name":"Tunable Floating-Point for Artificial Neural Networks","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2913598954","doi":"https://doi.org/10.1109/icecs.2018.8617900","mag":"2913598954"},"language":"en","primary_location":{"id":"doi:10.1109/icecs.2018.8617900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecs.2018.8617900","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","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/A5049409635","display_name":"Marta Franceschi","orcid":"https://orcid.org/0000-0002-0392-7907"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Marta Franceschi","raw_affiliation_strings":["DITEN, University of Genova, Italy"],"affiliations":[{"raw_affiliation_string":"DITEN, University of Genova, Italy","institution_ids":["https://openalex.org/I83816512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022318517","display_name":"Alberto Nannarelli","orcid":"https://orcid.org/0000-0002-8303-6329"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Alberto Nannarelli","raw_affiliation_strings":["DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark"],"affiliations":[{"raw_affiliation_string":"DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010811199","display_name":"Maurizio Valle","orcid":"https://orcid.org/0000-0002-7366-6060"},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Maurizio Valle","raw_affiliation_strings":["DITEN, University of Genova, Italy"],"affiliations":[{"raw_affiliation_string":"DITEN, University of Genova, Italy","institution_ids":["https://openalex.org/I83816512"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049409635"],"corresponding_institution_ids":["https://openalex.org/I83816512"],"apc_list":null,"apc_paid":null,"fwci":1.3308,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8556029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11325","display_name":"Inertial Sensor and Navigation","score":0.9886000156402588,"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/T11325","display_name":"Inertial Sensor and Navigation","score":0.9886000156402588,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9815000295639038,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.732018232345581},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6406936049461365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4668973386287689},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4603976309299469},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09570303559303284}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.732018232345581},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6406936049461365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4668973386287689},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4603976309299469},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09570303559303284},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icecs.2018.8617900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecs.2018.8617900","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unige.it:11567/983318","is_oa":false,"landing_page_url":"http://hdl.handle.net/11567/983318","pdf_url":null,"source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:pure.atira.dk:publications/551e92f4-ec9a-4546-92cd-29706f154886","is_oa":false,"landing_page_url":"https://orbit.dtu.dk/en/publications/551e92f4-ec9a-4546-92cd-29706f154886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Franceschi , M , Nannarelli , A &amp; Valle , M 2018 , Tunable Floating-Point for Artificial Neural Networks . in Proceedings of 25th IEEE International Conference on Electronics Circuits and Systems . IEEE , pp. 289-292 , 2018 IEEE 25th International Conference on Electronics, Circuits and Systems , Bordeaux , France , 09/12/2018 . https://doi.org/10.1109/ICECS.2018.8617900","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2119299853","https://openalex.org/W2266701264","https://openalex.org/W2519224033","https://openalex.org/W2525778437","https://openalex.org/W2553417306","https://openalex.org/W2606722458","https://openalex.org/W2743521949","https://openalex.org/W2890144054","https://openalex.org/W2891004123"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Approximate":[0],"computing":[1],"has":[2],"emerged":[3],"as":[4,18],"a":[5,83,111],"promising":[6],"approach":[7],"to":[8,67],"energy-efficient":[9],"design":[10],"of":[11,62,86,101,104],"digital":[12,19],"systems":[13],"in":[14,34,48,92,97,110],"many":[15],"domains":[16],"such":[17],"signal":[20],"processing,":[21],"robotics,":[22],"and":[23,90],"machine":[24],"learning.":[25],"Numerous":[26],"studies":[27],"report":[28],"that":[29],"employing":[30],"different":[31,73,76],"data":[32],"formats":[33],"Deep":[35],"Neural":[36],"Networks":[37],"(DNNs),":[38],"the":[39,60,93,99,105],"dominant":[40],"Machine":[41],"Learning":[42],"approach,":[43],"could":[44],"allow":[45],"substantial":[46],"improvements":[47],"power":[49,113],"efficiency":[50],"considering":[51],"an":[52],"acceptable":[53],"quality":[54],"for":[55,75,88],"results.":[56],"In":[57,71],"this":[58],"work,":[59],"application":[61],"Tunable":[63],"Floating-Point":[64],"(TFP)":[65],"precision":[66,100],"DNN":[68],"is":[69],"presented.":[70],"TFP":[72],"precisions":[74],"operations":[77],"can":[78],"be":[79],"set":[80],"by":[81],"selecting":[82],"specific":[84],"number":[85],"bits":[87],"significant":[89],"exponent":[91],"floating-point":[94],"representation.":[95],"Flexibility":[96],"tuning":[98],"given":[102],"layers":[103],"neural":[106],"network":[107],"may":[108],"result":[109],"more":[112],"efficient":[114],"computation.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-02-21T00:00:00"}
