{"id":"https://openalex.org/W2611984406","doi":"https://doi.org/10.23919/date.2017.7927265","title":"Synthesis of activation-parallel convolution structures for neuromorphic architectures","display_name":"Synthesis of activation-parallel convolution structures for neuromorphic architectures","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2611984406","doi":"https://doi.org/10.23919/date.2017.7927265","mag":"2611984406"},"language":"en","primary_location":{"id":"doi:10.23919/date.2017.7927265","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date.2017.7927265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE), 2017","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/A5040264872","display_name":"Seban Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seban Kim","raw_affiliation_strings":["Incheon National University, Incheon, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Incheon National University, Incheon, Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006563419","display_name":"Jaeyong Chung","orcid":"https://orcid.org/0000-0001-5819-1995"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeyong Chung","raw_affiliation_strings":["Incheon National University, Incheon, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Incheon National University, Incheon, Korea","institution_ids":["https://openalex.org/I146429904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1462,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49392515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"24","issue":null,"first_page":"1685","last_page":"1690"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9947999715805054,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.8908576965332031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8581795692443848},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6704249382019043},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.657715380191803},{"id":"https://openalex.org/keywords/loop-unrolling","display_name":"Loop unrolling","score":0.5489559173583984},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5044211149215698},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4789772033691406},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.42737337946891785},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.4257696270942688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35141974687576294},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3321927785873413},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.30154862999916077},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09094041585922241}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.8908576965332031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8581795692443848},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6704249382019043},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.657715380191803},{"id":"https://openalex.org/C76970557","wikidata":"https://www.wikidata.org/wiki/Q1869750","display_name":"Loop unrolling","level":3,"score":0.5489559173583984},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5044211149215698},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4789772033691406},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.42737337946891785},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.4257696270942688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35141974687576294},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3321927785873413},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.30154862999916077},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09094041585922241},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date.2017.7927265","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date.2017.7927265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE), 2017","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1501488688","https://openalex.org/W2024329410","https://openalex.org/W2040228209","https://openalex.org/W2138913040","https://openalex.org/W2141961492","https://openalex.org/W2163605009","https://openalex.org/W2183246402","https://openalex.org/W2194775991","https://openalex.org/W2257979135","https://openalex.org/W2399948372","https://openalex.org/W4231691742","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W3089892344","https://openalex.org/W2960220682","https://openalex.org/W4313442939","https://openalex.org/W4386227293","https://openalex.org/W4372267706","https://openalex.org/W2885510266","https://openalex.org/W4288055417","https://openalex.org/W4287758233","https://openalex.org/W3136467750","https://openalex.org/W3127981342"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,84],"networks":[2,85],"have":[3],"demonstrated":[4],"continued":[5],"success":[6],"in":[7,17],"various":[8],"visual":[9],"recognition":[10],"challenges.":[11],"The":[12],"convolutional":[13,40,83],"layers":[14,41],"are":[15,92],"implemented":[16],"the":[18,39,52,56,59,78,89,103,108,112],"activation-serial":[19],"or":[20,110],"fully":[21],"parallel":[22,36,48],"manner":[23],"on":[24,43],"neuromorphic":[25,97],"computing":[26,98],"systems.":[27],"This":[28,100],"paper":[29],"presents":[30],"an":[31],"unrolling":[32,57],"method":[33],"that":[34,102],"generates":[35],"structures":[37,91],"for":[38,55],"depending":[42],"a":[44,95],"required":[45],"level":[46],"of":[47,58],"processing.":[49],"We":[50,76],"analyze":[51],"resource":[53],"requirements":[54],"two-dimensional":[60],"filters,":[61],"and":[62,74,88],"propose":[63,79],"methods":[64,80,105],"to":[65,81],"deal":[66],"with":[67],"practical":[68,82],"considerations":[69],"such":[70],"as":[71],"stride,":[72],"borders,":[73],"alignment.":[75],"apply":[77],"including":[86],"AlexNet":[87],"generated":[90],"mapped":[93],"onto":[94],"recent":[96],"system.":[99],"demonstrates":[101],"proposed":[104],"can":[106],"improve":[107],"performance":[109],"reduce":[111],"power":[113],"consumption":[114],"significantly":[115],"even":[116],"without":[117],"area":[118],"penalty.":[119]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
