{"id":"https://openalex.org/W7135036250","doi":"https://doi.org/10.1088/2634-4386/ae5128","title":"Line-based event preprocessing: towards low-energy neuromorphic computer vision","display_name":"Line-based event preprocessing: towards low-energy neuromorphic computer vision","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135036250","doi":"https://doi.org/10.1088/2634-4386/ae5128"},"language":"en","primary_location":{"id":"doi:10.1088/2634-4386/ae5128","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/ae5128","pdf_url":null,"source":{"id":"https://openalex.org/S4210212933","display_name":"Neuromorphic Computing and Engineering","issn_l":"2634-4386","issn":["2634-4386"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neuromorphic Computing and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1088/2634-4386/ae5128","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038643925","display_name":"Am\u00e9lie Gruel","orcid":"https://orcid.org/0000-0003-3916-0514"},"institutions":[{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210166017","display_name":"Institut de Math\u00e9matiques de Bordeaux","ror":"https://ror.org/05m3r1b84","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I15057530","https://openalex.org/I4210141950","https://openalex.org/I4210160189","https://openalex.org/I4210166017"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Am\u00e9lie Gruel","raw_affiliation_strings":["Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, 33405, France"],"raw_orcid":"https://orcid.org/0000-0003-3916-0514","affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, 33405, France","institution_ids":["https://openalex.org/I4210166017","https://openalex.org/I15057530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046261820","display_name":"Pierre Lewden","orcid":"https://orcid.org/0009-0005-8311-8526"},"institutions":[{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pierre Lewden","raw_affiliation_strings":["Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me, Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, Nouvelle-Aquitaine, 33405, France"],"raw_orcid":"https://orcid.org/0009-0005-8311-8526","affiliations":[{"raw_affiliation_string":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me, Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, Nouvelle-Aquitaine, 33405, France","institution_ids":["https://openalex.org/I4210157089","https://openalex.org/I15057530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032494774","display_name":"Adrien F. Vincent","orcid":"https://orcid.org/0000-0002-9770-4236"},"institutions":[{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Adrien F Vincent","raw_affiliation_strings":["Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me, Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, Nouvelle-Aquitaine, 33405, France"],"raw_orcid":"https://orcid.org/0000-0002-9770-4236","affiliations":[{"raw_affiliation_string":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me, Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, Nouvelle-Aquitaine, 33405, France","institution_ids":["https://openalex.org/I4210157089","https://openalex.org/I15057530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128852107","display_name":"Sylvain Sa\u00efghi","orcid":null},"institutions":[{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sylvain Sa\u00efghi","raw_affiliation_strings":["Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me, Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, Nouvelle-Aquitaine, 33405, France"],"raw_orcid":"https://orcid.org/0000-0002-1414-2523","affiliations":[{"raw_affiliation_string":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me, Universit\u00e9 de Bordeaux, 351 Cours de la Lib\u00e9ration, Talence, Nouvelle-Aquitaine, 33405, France","institution_ids":["https://openalex.org/I4210157089","https://openalex.org/I15057530"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2000,"currency":"GBP","value_usd":2453},"apc_paid":{"value":2000,"currency":"GBP","value_usd":2453},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31818086,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"2","first_page":"024002","last_page":"024002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.930899977684021,"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":0.930899977684021,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.031199999153614044,"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":0.013100000098347664,"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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.980400025844574},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6554999947547913},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.620199978351593},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.6157000064849854},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5422000288963318},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5152999758720398},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4828999936580658},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4239000082015991}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.980400025844574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7685999870300293},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6554999947547913},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.620199978351593},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.6157000064849854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5945000052452087},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5422000288963318},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5152999758720398},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4828999936580658},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41909998655319214},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.3937000036239624},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.321399986743927},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31380000710487366},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2634-4386/ae5128","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/ae5128","pdf_url":null,"source":{"id":"https://openalex.org/S4210212933","display_name":"Neuromorphic Computing and Engineering","issn_l":"2634-4386","issn":["2634-4386"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neuromorphic Computing and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-05618444v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05618444","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Neuromorphic Computing and Engineering, 2026, 6 (2), pp.024002. ⟨10.1088/2634-4386/ae5128⟩","raw_type":"Journal articles"},{"id":"pmh:oai:doaj.org/article:5e1f8b23179c4697a7d3da7248c33b84","is_oa":true,"landing_page_url":"https://doaj.org/article/5e1f8b23179c4697a7d3da7248c33b84","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Neuromorphic Computing and Engineering, Vol 6, Iss 2, p 024002 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2634-4386/ae5128","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2634-4386/ae5128","pdf_url":null,"source":{"id":"https://openalex.org/S4210212933","display_name":"Neuromorphic Computing and Engineering","issn_l":"2634-4386","issn":["2634-4386"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neuromorphic Computing and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.9023982286453247,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G4165653413","display_name":null,"funder_award_id":"ANR-23-PEIA-0002","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1926086117","https://openalex.org/W2006370340","https://openalex.org/W2006495114","https://openalex.org/W2008625057","https://openalex.org/W2016574277","https://openalex.org/W2020096355","https://openalex.org/W2087861759","https://openalex.org/W2140886546","https://openalex.org/W2153041354","https://openalex.org/W2207801947","https://openalex.org/W2469278928","https://openalex.org/W2528596085","https://openalex.org/W2563042993","https://openalex.org/W2619510810","https://openalex.org/W2745933219","https://openalex.org/W2783525259","https://openalex.org/W2809335043","https://openalex.org/W2962804204","https://openalex.org/W2963200201","https://openalex.org/W2963497435","https://openalex.org/W2969407469","https://openalex.org/W3011302802","https://openalex.org/W3038702532","https://openalex.org/W3040838455","https://openalex.org/W3130213469","https://openalex.org/W3201870057","https://openalex.org/W4206609022","https://openalex.org/W4213351728","https://openalex.org/W4307438232","https://openalex.org/W4319300991","https://openalex.org/W4386911026","https://openalex.org/W4390187136","https://openalex.org/W4400811187","https://openalex.org/W4412651072","https://openalex.org/W7119492756"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Neuromorphic":[1],"vision":[2,172],"has":[3],"made":[4],"significant":[5,155],"progress":[6],"in":[7,22,58],"recent":[8],"years,":[9],"thanks":[10,173],"to":[11,61,74,91,108,153,174],"the":[12,48,67,75,120,125,128,139,145,158,164],"natural":[13],"match":[14],"between":[15,112],"spiking":[16],"neural":[17],"networks":[18],"and":[19,30,115,124],"event":[20,94,175],"data":[21,36,63,95],"terms":[23],"of":[24,70,77,127,157],"biological":[25],"inspiration,":[26],"energy":[27,41,68,113,147],"savings,":[28],"latency":[29],"memory":[31],"use":[32],"for":[33,51],"dynamic":[34],"visual":[35],"processing.":[37],"However,":[38],"optimising":[39],"its":[40],"requirements":[42],"still":[43],"remains":[44],"a":[45,154,167],"challenge":[46],"within":[47],"community,":[49],"especially":[50],"embedded":[52],"applications.":[53],"One":[54],"solution":[55],"may":[56],"reside":[57],"preprocessing":[59,106,122],"events":[60],"optimise":[62],"quantities":[64],"thus":[65,162],"lowering":[66],"cost":[69],"neuromorphic":[71,87,159,170],"hardware,":[72],"proportional":[73],"number":[76],"synaptic":[78],"operations.":[79],"To":[80],"this":[81],"end,":[82],"we":[83,131],"extend":[84],"an":[85,109],"end-to-end":[86],"line":[88],"detection":[89],"mechanism":[90],"introduce":[92],"line-based":[93,121],"preprocessing.":[96,176],"Our":[97,149],"results":[98],"demonstrate":[99],"on":[100,119],"three":[101],"benchmark":[102],"event-based":[103],"datasets":[104],"that":[105,133],"leads":[107,152],"advantageous":[110],"trade-off":[111],"consumption":[114],"classification":[116,129,140,160],"performance.":[117],"Depending":[118],"strategy":[123],"complexity":[126],"task,":[130],"show":[132],"one":[134],"can":[135],"maintain":[136],"or":[137],"increase":[138],"accuracy":[141],"while":[142],"significantly":[143],"reducing":[144],"theoretical":[146],"consumption.":[148],"approach":[150],"systematically":[151],"improvement":[156],"efficiency,":[161],"laying":[163],"groundwork":[165],"towards":[166],"more":[168],"frugal":[169],"computer":[171]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-13T00:00:00"}