{"id":"https://openalex.org/W4403443927","doi":"https://doi.org/10.48550/arxiv.2410.08229","title":"Improving Spiking Neural Network Accuracy With Color Model Information\n Encoded Bit Planes","display_name":"Improving Spiking Neural Network Accuracy With Color Model Information\n Encoded Bit Planes","publication_year":2024,"publication_date":"2024-09-28","ids":{"openalex":"https://openalex.org/W4403443927","doi":"https://doi.org/10.48550/arxiv.2410.08229"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.08229","pdf_url":"http://arxiv.org/pdf/2410.08229","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2410.08229","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090044114","display_name":"Nhan T. Luu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luu, Nhan T.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110070160","display_name":"Thang C. Truong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Truong, Thang C.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5060314791","display_name":"Doan\u2010Trung Luu","orcid":"https://orcid.org/0000-0001-9765-2125"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luu, Duong T.","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":77},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9919,"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":0.9919,"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/T10320","display_name":"Neural Networks and Applications","score":0.974,"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":0.9217,"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/bit","display_name":"Bit (key)","score":0.6572409}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.67933345},{"id":"https://openalex.org/C117011727","wikidata":"https://www.wikidata.org/wiki/Q1278488","display_name":"Bit (key)","level":2,"score":0.6572409},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6156377},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.56596655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5533271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38784587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36955857},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15350765}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.08229","pdf_url":"http://arxiv.org/pdf/2410.08229","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.08229","pdf_url":"http://arxiv.org/pdf/2410.08229","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4394546135","https://openalex.org/W4381186982","https://openalex.org/W4285347720","https://openalex.org/W4226055750","https://openalex.org/W4200259850","https://openalex.org/W2484894494","https://openalex.org/W2411923897","https://openalex.org/W2367385042","https://openalex.org/W2333831899","https://openalex.org/W2040781570"],"abstract_inverted_index":{"Spiking":[0],"neural":[1],"networks":[2],"(SNNs)":[3],"have":[4],"emerged":[5],"as":[6,19],"a":[7,47,57],"promising":[8],"paradigm":[9],"in":[10,109,152,166],"computational":[11,85],"neuroscience":[12],"and":[13,23,162,169],"artificial":[14],"intelligence,":[15],"offering":[16],"advantages":[17],"such":[18],"low":[20],"energy":[21],"consumption":[22],"small":[24],"memory":[25],"footprint.":[26],"However,":[27],"their":[28],"practical":[29],"adoption":[30],"is":[31,80,125],"constrained":[32],"by":[33],"several":[34],"challenges,":[35],"prominently":[36],"among":[37],"them":[38],"being":[39],"performance":[40,53,111],"optimization.":[41],"In":[42],"this":[43,124],"study,":[44],"we":[45,101,146],"present":[46],"novel":[48],"approach":[49],"to":[50,82,90,148],"enhance":[51],"the":[52,84,103,119,126,134,140,157],"of":[54,70,87,105,121,136,143],"SNNs":[55,88,153,164],"through":[56],"new":[58,150],"encoding":[59,107],"method":[60],"that":[61],"exploits":[62],"bit":[63],"planes":[64],"derived":[65],"from":[66],"various":[67],"color":[68,131,144],"models":[69,165],"input":[71],"image":[72],"data":[73],"for":[74,159],"spike":[75],"encoding.":[76],"Our":[77],"proposed":[78],"technique":[79],"designed":[81],"improve":[83],"accuracy":[86],"compared":[89],"conventional":[91],"methods":[92],"without":[93],"increasing":[94],"model":[95],"size.":[96],"Through":[97],"extensive":[98],"experimental":[99],"validation,":[100],"demonstrate":[102],"effectiveness":[104],"our":[106,122],"strategy":[108],"achieving":[110],"gain":[112],"across":[113],"multiple":[114],"computer":[115],"vision":[116],"tasks.":[117],"To":[118],"best":[120],"knowledge,":[123],"first":[127],"research":[128],"endeavor":[129],"applying":[130],"spaces":[132],"within":[133],"context":[135],"SNNs.":[137],"By":[138],"leveraging":[139],"unique":[141],"characteristics":[142],"spaces,":[145],"hope":[147],"unlock":[149],"potentials":[151],"performance,":[154],"potentially":[155],"paving":[156],"way":[158],"more":[160],"efficient":[161],"effective":[163],"future":[167],"researches":[168],"applications.":[170]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4403443927","counts_by_year":[],"updated_date":"2025-04-23T19:05:43.191252","created_date":"2024-10-16"}