{"id":"https://openalex.org/W3035000326","doi":"https://doi.org/10.24963/ijcai.2020/211","title":"LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition","display_name":"LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3035000326","doi":"https://doi.org/10.24963/ijcai.2020/211","mag":"3035000326"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/211","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/211","pdf_url":"https://www.ijcai.org/proceedings/2020/0211.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0211.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011261818","display_name":"Xiang Cheng","orcid":"https://orcid.org/0000-0003-3246-7062"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210164150","display_name":"Shanghai Center for Brain Science and Brain-Inspired Technology","ror":"https://ror.org/0551a0y31","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210164150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Cheng","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","Research Center for Brain-inspired Intelligence, CASIA","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"Research Center for Brain-inspired Intelligence, CASIA","institution_ids":["https://openalex.org/I4210164150"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059162334","display_name":"Yunzhe Hao","orcid":"https://orcid.org/0000-0001-7824-6965"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210164150","display_name":"Shanghai Center for Brain Science and Brain-Inspired Technology","ror":"https://ror.org/0551a0y31","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210164150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunzhe Hao","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","Research Center for Brain-inspired Intelligence, CASIA","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"Research Center for Brain-inspired Intelligence, CASIA","institution_ids":["https://openalex.org/I4210164150"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101746187","display_name":"Jiaming Xu","orcid":"https://orcid.org/0000-0001-7635-1059"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210164150","display_name":"Shanghai Center for Brain Science and Brain-Inspired Technology","ror":"https://ror.org/0551a0y31","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210164150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaming Xu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","Research Center for Brain-inspired Intelligence, CASIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"Research Center for Brain-inspired Intelligence, CASIA","institution_ids":["https://openalex.org/I4210164150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108642431","display_name":"Bo Xu","orcid":"https://orcid.org/0000-0002-1111-1529"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210097554","display_name":"Center for Excellence in Brain Science and Intelligence Technology","ror":"https://ror.org/00vpwhm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210097554"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210164150","display_name":"Shanghai Center for Brain Science and Brain-Inspired Technology","ror":"https://ror.org/0551a0y31","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210164150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Xu","raw_affiliation_strings":["Center for Excellence in Brain Science and Intelligence Technology, CAS. China","Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","Research Center for Brain-inspired Intelligence, CASIA","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Excellence in Brain Science and Intelligence Technology, CAS. China","institution_ids":["https://openalex.org/I4210097554"]},{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences (CASIA). Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"Research Center for Brain-inspired Intelligence, CASIA","institution_ids":["https://openalex.org/I4210164150"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":115,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1519","last_page":"1525"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9987000226974487,"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/mnist-database","display_name":"MNIST database","score":0.982129693031311},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8715159893035889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7689701318740845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6449713706970215},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.6441302299499512},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6089247465133667},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5394206047058105},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5340731739997864},{"id":"https://openalex.org/keywords/biological-neuron-model","display_name":"Biological neuron model","score":0.5008418560028076},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45133525133132935},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4334167540073395},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42838823795318604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3953372836112976},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33766430616378784},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.2744510769844055}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.982129693031311},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8715159893035889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7689701318740845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6449713706970215},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.6441302299499512},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6089247465133667},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5394206047058105},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5340731739997864},{"id":"https://openalex.org/C186565885","wikidata":"https://www.wikidata.org/wiki/Q1651163","display_name":"Biological neuron model","level":3,"score":0.5008418560028076},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45133525133132935},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4334167540073395},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42838823795318604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3953372836112976},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33766430616378784},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2744510769844055},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/211","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/211","pdf_url":"https://www.ijcai.org/proceedings/2020/0211.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/211","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/211","pdf_url":"https://www.ijcai.org/proceedings/2020/0211.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G8837481101","display_name":null,"funder_award_id":"XDB32070000","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"}],"funders":[{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035000326.pdf","grobid_xml":"https://content.openalex.org/works/W3035000326.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1570411240","https://openalex.org/W2059148040","https://openalex.org/W2093910183","https://openalex.org/W2100495367","https://openalex.org/W2103179919","https://openalex.org/W2112796928","https://openalex.org/W2132385194","https://openalex.org/W2313320147","https://openalex.org/W2504024651","https://openalex.org/W2513853720","https://openalex.org/W2547418827","https://openalex.org/W2621826044","https://openalex.org/W2750384547","https://openalex.org/W2765204015","https://openalex.org/W2779025322","https://openalex.org/W2792643794","https://openalex.org/W2799049915","https://openalex.org/W2808594940","https://openalex.org/W2891530223","https://openalex.org/W2892077605","https://openalex.org/W2898323475","https://openalex.org/W2904620099","https://openalex.org/W2905533880","https://openalex.org/W2919115771","https://openalex.org/W2951305674","https://openalex.org/W2962684665","https://openalex.org/W2962804204","https://openalex.org/W2963760575","https://openalex.org/W2963830987","https://openalex.org/W2963834742","https://openalex.org/W2970338293","https://openalex.org/W2971783054","https://openalex.org/W3015205410","https://openalex.org/W4298355310"],"related_works":["https://openalex.org/W3214713078","https://openalex.org/W3161396968","https://openalex.org/W2183631084","https://openalex.org/W3202412105","https://openalex.org/W4287120180","https://openalex.org/W3169602696","https://openalex.org/W4287639722","https://openalex.org/W4380324631","https://openalex.org/W3156786002","https://openalex.org/W4200249236"],"abstract_inverted_index":{"Spiking":[0,70],"Neural":[1,71],"Network":[2,72],"(SNN)":[3],"is":[4],"considered":[5],"more":[6],"biologically":[7,178],"plausible":[8,179],"and":[9,30,68,89,128,158],"energy-efficient":[10],"on":[11,76,104,131,155],"emerging":[12],"neuromorphic":[13],"hardware.":[14],"Recently":[15],"backpropagation":[16,124],"algorithm":[17],"has":[18],"been":[19],"utilized":[20],"for":[21,39],"training":[22],"SNN,":[23,79,182],"which":[24,49],"allows":[25],"SNN":[26,37,103],"to":[27,117,125,149,163],"go":[28],"deeper":[29],"achieve":[31,143],"higher":[32],"performance.":[33],"However,":[34],"most":[35],"existing":[36],"models":[38],"object":[40],"recognition":[41],"are":[42],"mainly":[43],"convolutional":[44,78],"structures":[45],"or":[46,145],"fully-connected":[47],"structures,":[48],"only":[50],"have":[51],"inter-layer":[52],"connections,":[53],"but":[54],"no":[55],"intra-layer":[56],"connections.":[57],"Inspired":[58],"by":[59],"Lateral":[60],"Interactions":[61],"in":[62,194],"neuroscience,":[63],"we":[64,80],"propose":[65],"a":[66,101,105,177],"high-performance":[67],"noise-robust":[69],"(dubbed":[73],"LISNN).":[74],"Based":[75],"the":[77,82,93,114,119,139,190,195],"model":[81,141,167],"lateral":[83,164],"interactions":[84],"between":[85],"spatially":[86],"adjacent":[87],"neurons":[88],"integrate":[90],"it":[91,185],"into":[92,181],"spiking":[94,152],"neuron":[95],"membrane":[96],"potential":[97],"formula,":[98],"then":[99],"build":[100],"multi-layer":[102],"popular":[106],"deep":[107],"learning":[108],"framework,":[109],"i.\\,e.,":[110],"PyTorch.":[111],"We":[112],"utilize":[113],"pseudo-derivative":[115],"method":[116],"solve":[118],"non-differentiable":[120],"problem":[121],"when":[122],"applying":[123],"train":[126],"LISNN":[127,130],"test":[129],"multiple":[132],"standard":[133],"datasets.":[134,160],"Experimental":[135],"results":[136],"demonstrate":[137],"that":[138,184],"proposed":[140],"can":[142,186],"competitive":[144],"better":[146],"performance":[147],"compared":[148],"current":[150],"state-of-the-art":[151],"neural":[153],"networks":[154],"MNIST,":[156],"Fashion-MNIST,":[157],"N-MNIST":[159],"Besides,":[161],"thanks":[162],"interactions,":[165],"our":[166],"processes":[168],"stronger":[169],"noise-robustness":[170],"than":[171],"other":[172],"SNN.":[173],"Our":[174],"work":[175],"brings":[176],"mechanism":[180],"hoping":[183],"help":[187],"us":[188],"understand":[189],"visual":[191],"information":[192],"processing":[193],"brain.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":34},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}