{"id":"https://openalex.org/W4403295770","doi":"https://doi.org/10.1109/tpami.2024.3467709","title":"Fast Window-Based Event Denoising With Spatiotemporal Correlation Enhancement","display_name":"Fast Window-Based Event Denoising With Spatiotemporal Correlation Enhancement","publication_year":2024,"publication_date":"2024-10-10","ids":{"openalex":"https://openalex.org/W4403295770","doi":"https://doi.org/10.1109/tpami.2024.3467709","pmid":"https://pubmed.ncbi.nlm.nih.gov/39388326"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3467709","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3467709","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5069518140","display_name":"Huachen Fang","orcid":"https://orcid.org/0000-0001-8678-6822"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huachen Fang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074780876","display_name":"Jinjian Wu","orcid":"https://orcid.org/0000-0001-7501-0009"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjian Wu","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040392623","display_name":"Qibin Hou","orcid":"https://orcid.org/0000-0002-8388-8708"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qibin Hou","raw_affiliation_strings":["VCIP, School of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"VCIP, School of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037310802","display_name":"Weisheng Dong","orcid":"https://orcid.org/0000-0002-9632-985X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weisheng Dong","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101549504","display_name":"Guangming Shi","orcid":"https://orcid.org/0000-0003-2179-3292"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangming Shi","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5069518140"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.366,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.8451227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"47","issue":"3","first_page":"1381","last_page":"1394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8877999782562256,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8877999782562256,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.8720999956130981,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.820900022983551,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.641227126121521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6181570887565613},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5826225280761719},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5506609082221985},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4696986675262451},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.4256429970264435},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35515743494033813},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2612687051296234}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.641227126121521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6181570887565613},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5826225280761719},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5506609082221985},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4696986675262451},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.4256429970264435},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35515743494033813},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2612687051296234},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2024.3467709","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3467709","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:39388326","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39388326","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1016030804","display_name":null,"funder_award_id":"QTZX23038","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W206948248","https://openalex.org/W1484764436","https://openalex.org/W1568383588","https://openalex.org/W1768306949","https://openalex.org/W2141840773","https://openalex.org/W2149211411","https://openalex.org/W2194775991","https://openalex.org/W2343449569","https://openalex.org/W2499758651","https://openalex.org/W2519559998","https://openalex.org/W2530906228","https://openalex.org/W2563042993","https://openalex.org/W2596572706","https://openalex.org/W2602186967","https://openalex.org/W2619510810","https://openalex.org/W2745933219","https://openalex.org/W2766452532","https://openalex.org/W2782061689","https://openalex.org/W2796368857","https://openalex.org/W2884195444","https://openalex.org/W2947930228","https://openalex.org/W2963510238","https://openalex.org/W2967086581","https://openalex.org/W2972000740","https://openalex.org/W3010556452","https://openalex.org/W3011302802","https://openalex.org/W3011746063","https://openalex.org/W3024044537","https://openalex.org/W3034469298","https://openalex.org/W3035234594","https://openalex.org/W3103312471","https://openalex.org/W3191528047","https://openalex.org/W3199425519","https://openalex.org/W4206567210","https://openalex.org/W4213412898","https://openalex.org/W4221138189","https://openalex.org/W4253803843","https://openalex.org/W4295909205","https://openalex.org/W4304099187","https://openalex.org/W4360584268","https://openalex.org/W4385819596","https://openalex.org/W6606171110","https://openalex.org/W6674987968","https://openalex.org/W6682751323","https://openalex.org/W6739778489","https://openalex.org/W6770774428","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2109115373","https://openalex.org/W2390901981","https://openalex.org/W4230691760","https://openalex.org/W4391923333","https://openalex.org/W2393847170","https://openalex.org/W85049056","https://openalex.org/W158465905","https://openalex.org/W577521963","https://openalex.org/W2054277467","https://openalex.org/W38405698"],"abstract_inverted_index":{"Previous":[0],"deep":[1],"learning-based":[2],"event":[3,28,45,79,102,148,188],"denoising":[4,41,149,155,169],"methods":[5],"mostly":[6],"suffer":[7],"from":[8],"poor":[9],"interpretability":[10],"and":[11,61,77,85,103,105,128,138,142,157,179,191,193],"difficulty":[12],"in":[13,58,170],"real-time":[14,168],"processing":[15,75],"due":[16],"to":[17,64,80,99,112,135,166],"their":[18],"complex":[19,171],"architecture":[20],"designs.":[21],"In":[22,67,90],"this":[23],"paper,":[24],"we":[25,49,70,93,122],"propose":[26],"window-based":[27,147],"denoising,":[29],"which":[30],"simultaneously":[31],"deals":[32],"with":[33],"a":[34,96,144],"stack":[35],"of":[36,161,181,197],"events":[37,76],"while":[38],"existing":[39],"element-based":[40],"focuses":[42],"on":[43,55,118],"one":[44],"each":[46],"time.":[47],"Besides,":[48],"give":[50],"the":[51,82,107,114,119,177,195],"theoretical":[52,120],"analysis":[53],"based":[54],"probability":[56],"distributions":[57],"both":[59],"temporal":[60,68,83,137],"spatial":[62,91,139],"domains":[63],"improve":[65,194],"interpretability.":[66],"domain,":[69,92],"use":[71,106],"timestamp":[72],"deviations":[73],"between":[74],"central":[78],"judge":[81],"correlation":[84],"filter":[86],"out":[87],"temporal-irrelevant":[88],"events.":[89],"choose":[94],"maximum":[95],"posteriori":[97],"(MAP)":[98],"discriminate":[100],"real-world":[101],"noise":[104,189],"learned":[108],"convolutional":[109],"sparse":[110],"coding":[111],"optimize":[113],"objective":[115],"function.":[116],"Based":[117],"analysis,":[121],"build":[123],"Temporal":[124],"Window":[125],"(TW)":[126],"module":[127,134],"Soft":[129],"Spatial":[130],"Feature":[131],"Embedding":[132],"(SSFE)":[133],"process":[136],"information":[140],"separately,":[141],"construct":[143],"novel":[145],"multi-scale":[146],"network,":[150],"named":[151],"WedNet.":[152,183],"The":[153],"high":[154],"accuracy":[156],"fast":[158],"running":[159],"speed":[160],"our":[162,182],"WedNet":[163],"enables":[164],"us":[165],"achieve":[167],"scenes.":[172],"Extensive":[173],"experimental":[174],"results":[175],"verify":[176],"effectiveness":[178],"robustness":[180],"Our":[184],"algorithm":[185],"can":[186],"remove":[187],"effectively":[190],"efficiently":[192],"performance":[196],"downstream":[198],"tasks.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}