{"id":"https://openalex.org/W4394698802","doi":"https://doi.org/10.1109/tnnls.2024.3377717","title":"TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks","display_name":"TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks","publication_year":2024,"publication_date":"2024-04-10","ids":{"openalex":"https://openalex.org/W4394698802","doi":"https://doi.org/10.1109/tnnls.2024.3377717","pmid":"https://pubmed.ncbi.nlm.nih.gov/38598397"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3377717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3377717","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5027563148","display_name":"Ruijie Zhu","orcid":"https://orcid.org/0000-0003-1210-546X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Rui-Jie Zhu","raw_affiliation_strings":["University of California, Santa Cruz, Santa Cruz, CA, USA","University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Cruz, Santa Cruz, CA, USA","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031886937","display_name":"Malu Zhang","orcid":"https://orcid.org/0000-0002-2345-0974"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Malu Zhang","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-2345-0974","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055884721","display_name":"Qihang Zhao","orcid":"https://orcid.org/0000-0002-8431-5389"},"institutions":[{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qihang Zhao","raw_affiliation_strings":["Kuaishou Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kuaishou Technology, Beijing, China","institution_ids":["https://openalex.org/I4401726859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101824758","display_name":"Haoyu Deng","orcid":"https://orcid.org/0000-0001-6637-0619"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-6637-0619","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033398332","display_name":"Yule Duan","orcid":"https://orcid.org/0000-0002-2505-8730"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yule Duan","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088224232","display_name":"Liang-Jian Deng","orcid":"https://orcid.org/0000-0003-3178-9772"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang-Jian Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3178-9772","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.9529,"has_fulltext":false,"cited_by_count":84,"citation_normalized_percentile":{"value":0.99066777,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"36","issue":"3","first_page":"5112","last_page":"5125"},"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":0.9986000061035156,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9973000288009644,"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/spiking-neural-network","display_name":"Spiking neural network","score":0.8157644271850586},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7975530624389648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5714693069458008},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.5669426918029785},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.5408210754394531},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44356605410575867},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.415299654006958},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3514025807380676},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3194124102592468}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8157644271850586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7975530624389648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5714693069458008},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.5669426918029785},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.5408210754394531},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44356605410575867},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.415299654006958},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3514025807380676},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3194124102592468}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3377717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3377717","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38598397","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38598397","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G1628077028","display_name":null,"funder_award_id":"2020YFA0714001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G2129173210","display_name":null,"funder_award_id":"12271083","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3778334585","display_name":null,"funder_award_id":"12171072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5706525165","display_name":null,"funder_award_id":"62106038","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W1596035946","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1999085092","https://openalex.org/W2020676607","https://openalex.org/W2095705004","https://openalex.org/W2119610790","https://openalex.org/W2155904486","https://openalex.org/W2164653071","https://openalex.org/W2513853720","https://openalex.org/W2619510810","https://openalex.org/W2621826044","https://openalex.org/W2745933219","https://openalex.org/W2750384547","https://openalex.org/W2892077605","https://openalex.org/W2908199053","https://openalex.org/W2908510526","https://openalex.org/W2962804204","https://openalex.org/W2963144106","https://openalex.org/W2963420686","https://openalex.org/W2963510238","https://openalex.org/W2984844508","https://openalex.org/W2990793844","https://openalex.org/W3022766987","https://openalex.org/W3025773901","https://openalex.org/W3035000326","https://openalex.org/W3102040318","https://openalex.org/W3102750118","https://openalex.org/W3118608800","https://openalex.org/W3124546450","https://openalex.org/W3162489473","https://openalex.org/W3186268528","https://openalex.org/W3186962187","https://openalex.org/W3196571547","https://openalex.org/W3200729277","https://openalex.org/W3201870057","https://openalex.org/W3203040596","https://openalex.org/W3203196551","https://openalex.org/W3208650852","https://openalex.org/W3217350819","https://openalex.org/W4221155907","https://openalex.org/W4224289525","https://openalex.org/W4224329724","https://openalex.org/W4226179567","https://openalex.org/W4238614602","https://openalex.org/W4289752563","https://openalex.org/W4312527777","https://openalex.org/W4313181051","https://openalex.org/W4362691888","https://openalex.org/W4378086185","https://openalex.org/W4382450050","https://openalex.org/W4382657974","https://openalex.org/W4386322090","https://openalex.org/W4387929535","https://openalex.org/W4388633184","https://openalex.org/W4388819746","https://openalex.org/W4389776595","https://openalex.org/W4393154986","https://openalex.org/W6602394311","https://openalex.org/W6637373629","https://openalex.org/W6674330103","https://openalex.org/W6729983426","https://openalex.org/W6743688258","https://openalex.org/W6745136726","https://openalex.org/W6749922295","https://openalex.org/W6754595668","https://openalex.org/W6757817989","https://openalex.org/W6766330063","https://openalex.org/W6766978945","https://openalex.org/W6787972765","https://openalex.org/W6796939779","https://openalex.org/W6803524348","https://openalex.org/W6809648081","https://openalex.org/W6809675958","https://openalex.org/W6810488471","https://openalex.org/W6810894145","https://openalex.org/W6846258938","https://openalex.org/W6856972904","https://openalex.org/W6869768396"],"related_works":["https://openalex.org/W3137378424","https://openalex.org/W2809732489","https://openalex.org/W4287780255","https://openalex.org/W3023361272","https://openalex.org/W4393235919","https://openalex.org/W4281699635","https://openalex.org/W4321472116","https://openalex.org/W3036048022","https://openalex.org/W3202619090","https://openalex.org/W4309224979"],"abstract_inverted_index":{"Spiking":[0],"neural":[1,30],"networks":[2],"(SNNs)":[3],"are":[4,244],"attracting":[5],"widespread":[6],"interest":[7],"due":[8],"to":[9,43,64,99,120,145,206],"their":[10],"biological":[11],"plausibility,":[12],"energy":[13],"efficiency,":[14],"and":[15,37,46,82,128,132,152,165,186,196,237],"powerful":[16],"spatiotemporal":[17],"information":[18],"representation":[19],"ability.":[20],"Given":[21],"the":[22,33,74,96,101,126,136,147,150,159,167,175,179,203,216,224,228],"critical":[23],"role":[24],"of":[25,35,76,161,218],"attention":[26,38,59,113],"mechanisms":[27,39,114],"in":[28],"enhancing":[29],"network":[31],"performance,":[32],"integration":[34],"SNNs":[36],"exhibits":[40],"tremendous":[41],"potential":[42],"deliver":[44],"energy-efficient":[45],"high-performance":[47],"computing":[48],"paradigms.":[49],"In":[50],"this":[51,221],"article,":[52],"we":[53,94,109,134,200],"present":[54],"a":[55,142,212],"novel":[56,143],"temporal-channel":[57],"joint":[58],"mechanism":[60,230],"for":[61,234],"SNNs,":[62],"referred":[63],"as":[65,141],"TCJA-SNN.":[66],"The":[67],"proposed":[68,176],"TCJA-SNN":[69,177,204],"framework":[70,205],"can":[71],"effectively":[72,157,201],"assess":[73],"significance":[75],"spike":[77,102],"sequence":[78],"from":[79],"both":[80],"spatial":[81],"temporal":[83,127,151],"dimensions.":[84],"More":[85],"specifically,":[86],"our":[87,219],"essential":[88],"technical":[89],"contribution":[90],"lies":[91],"on:":[92],"1)":[93],"employ":[95],"squeeze":[97],"operation":[98],"compress":[100],"stream":[103],"into":[104],"an":[105],"average":[106],"matrix.":[107],"Then,":[108],"leverage":[110],"two":[111,163],"local":[112],"based":[115],"on":[116,182],"efficient":[117],"1-D":[118],"convolutions":[119],"facilitate":[121],"comprehensive":[122],"feature":[123],"extraction":[124],"at":[125,246],"channel":[129,153],"levels":[130],"independently":[131],"2)":[133],"introduce":[135],"cross-convolutional":[137],"fusion":[138],"(CCF)":[139],"layer":[140,156],"approach":[144],"model":[146],"interdependencies":[148],"between":[149,169],"scopes.":[154],"This":[155],"breaks":[158],"independence":[160],"these":[162],"dimensions":[164],"enables":[166],"interaction":[168],"features.":[170],"Experimental":[171],"results":[172],"demonstrate":[173],"that":[174],"outperforms":[178],"state-of-the-art":[180],"(SOTA)":[181],"all":[183],"standard":[184],"static":[185],"neuromorphic":[187],"datasets,":[188],"including":[189],"Fashion-MNIST,":[190],"CIFAR10,":[191],"CIFAR100,":[192],"CIFAR10-DVS,":[193],"N-Caltech":[194],"101,":[195],"DVS128":[197],"Gesture.":[198],"Furthermore,":[199],"apply":[202],"image":[207],"generation":[208,239],"tasks":[209],"by":[210],"leveraging":[211],"variation":[213],"autoencoder.":[214],"To":[215],"best":[217],"knowledge,":[220],"study":[222],"is":[223],"first":[225],"instance":[226],"where":[227],"SNN-attention":[229],"has":[231],"been":[232],"employed":[233],"high-level":[235],"classification":[236],"low-level":[238],"tasks.":[240],"Our":[241],"implementation":[242],"codes":[243],"available":[245],"https://github.com/ridgerchu/TCJA.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":49},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}