{"id":"https://openalex.org/W7129289420","doi":"https://doi.org/10.1109/icipw68931.2025.11386327","title":"Multi-View Analysis: Back to the Classic with A NN Twist","display_name":"Multi-View Analysis: Back to the Classic with A NN Twist","publication_year":2025,"publication_date":"2025-09-14","ids":{"openalex":"https://openalex.org/W7129289420","doi":"https://doi.org/10.1109/icipw68931.2025.11386327"},"language":null,"primary_location":{"id":"doi:10.1109/icipw68931.2025.11386327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icipw68931.2025.11386327","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Image Processing Workshops (ICIPW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5126185787","display_name":"Lei Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092976","display_name":"Metropolitan University","ror":"https://ror.org/00ewfne71","country_code":"RS","type":"education","lineage":["https://openalex.org/I4210092976"]}],"countries":["RS"],"is_corresponding":true,"raw_author_name":"Lei Gao","raw_affiliation_strings":["Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada"],"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada","institution_ids":["https://openalex.org/I4210092976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126191810","display_name":"Kai Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092976","display_name":"Metropolitan University","ror":"https://ror.org/00ewfne71","country_code":"RS","type":"education","lineage":["https://openalex.org/I4210092976"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Kai Liu","raw_affiliation_strings":["Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada"],"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada","institution_ids":["https://openalex.org/I4210092976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088411692","display_name":"Zheng Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092976","display_name":"Metropolitan University","ror":"https://ror.org/00ewfne71","country_code":"RS","type":"education","lineage":["https://openalex.org/I4210092976"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Zheng Guo","raw_affiliation_strings":["Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada"],"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada","institution_ids":["https://openalex.org/I4210092976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111419869","display_name":"Ling Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092976","display_name":"Metropolitan University","ror":"https://ror.org/00ewfne71","country_code":"RS","type":"education","lineage":["https://openalex.org/I4210092976"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Ling Guan","raw_affiliation_strings":["Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada"],"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University Toronto,Computer and Biomedical Engineering,Department of Electrical,Canada","institution_ids":["https://openalex.org/I4210092976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126185787"],"corresponding_institution_ids":["https://openalex.org/I4210092976"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75276087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"696","last_page":"701"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.27250000834465027,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.27250000834465027,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.2556999921798706,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.11100000143051147,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5314000248908997},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.46299999952316284},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.46059998869895935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43860000371932983},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.42879998683929443},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.41350001096725464},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4129999876022339},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36160001158714294}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6937000155448914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6262999773025513},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5314000248908997},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.46299999952316284},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.42879998683929443},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39739999175071716},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C87868495","wikidata":"https://www.wikidata.org/wiki/Q750843","display_name":"Information processing","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C2776196297","wikidata":"https://www.wikidata.org/wiki/Q17138781","display_name":"Twist","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26910001039505005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26829999685287476},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icipw68931.2025.11386327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icipw68931.2025.11386327","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Image Processing Workshops (ICIPW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6471263766288757}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2028880308","https://openalex.org/W2049466529","https://openalex.org/W2126685080","https://openalex.org/W2474352580","https://openalex.org/W2551607540","https://openalex.org/W2570903723","https://openalex.org/W2737498981","https://openalex.org/W2803386491","https://openalex.org/W2911790834","https://openalex.org/W2912311811","https://openalex.org/W2944006115","https://openalex.org/W2962902633","https://openalex.org/W2963084307","https://openalex.org/W2963155035","https://openalex.org/W2973131617","https://openalex.org/W2994762555","https://openalex.org/W2998070674","https://openalex.org/W3014975538","https://openalex.org/W3015814965","https://openalex.org/W3016237565","https://openalex.org/W3035463153","https://openalex.org/W3038021356","https://openalex.org/W3097724114","https://openalex.org/W3158243908","https://openalex.org/W3159134235","https://openalex.org/W3177071754","https://openalex.org/W3213518743","https://openalex.org/W4200071390","https://openalex.org/W4214634256","https://openalex.org/W4229025198","https://openalex.org/W4244096624","https://openalex.org/W4282943820","https://openalex.org/W4295136088","https://openalex.org/W4308742494","https://openalex.org/W4312245820","https://openalex.org/W4313887231","https://openalex.org/W4319299930","https://openalex.org/W4321605968","https://openalex.org/W4322743975","https://openalex.org/W4367721852","https://openalex.org/W4376116550","https://openalex.org/W4378977821","https://openalex.org/W4386065571","https://openalex.org/W4386917298","https://openalex.org/W4388073267","https://openalex.org/W4390327397","https://openalex.org/W4390871806","https://openalex.org/W4392980425","https://openalex.org/W4393148719","https://openalex.org/W4407925568"],"related_works":[],"abstract_inverted_index":{"Acknowledging":[0],"the":[1,32,36,105,108,124,138,156],"tremendous":[2],"contributions":[3],"deep":[4],"learning":[5],"(DL)":[6],"made":[7],"to":[8,44,60,115,118,141],"a":[9,42,75,79,83,87,96,151,159],"broad":[10],"range":[11],"of":[12,31,110,137,167],"image,":[13],"video":[14],"and":[15,25,155,171],"multimedia":[16],"processing":[17,99,190],"tasks":[18],"(such":[19],"as":[20,128],"image":[21],"classification,":[22],"visual":[23],"tracking":[24],"cross-modal":[26],"retrieval),":[27],"further":[28],"optimizing":[29],"quality":[30],"features":[33,145],"extracted":[34],"by":[35],"DL":[37,54],"algorithms":[38],"has":[39],"consistently":[40],"presented":[41],"challenge":[43],"reckon":[45],"with,":[46,143],"especially":[47],"when":[48],"working":[49],"with":[50,86,121,150,158,193],"multi-view":[51,98,169],"data.":[52],"Though":[53],"models":[55],"have":[56,67],"been":[57,68],"hotly":[58],"pursued":[59],"address":[61],"this":[62,71,177],"issue,":[63],"no":[64],"clear":[65],"breakthroughs":[66],"witnessed.":[69],"In":[70],"work,":[72],"we":[73],"present":[74],"recent":[76],"development":[77,109],"from":[78,165],"significantly":[80],"different":[81],"perspective,":[82],"classic":[84],"approach":[85,93,178],"neural":[88],"network":[89],"(NN)":[90],"twist.":[91],"This":[92],"calls":[94],"upon":[95],"natural":[97],"architecture,":[100],"discriminant":[101,129],"correlation":[102,131],"analysis,":[103],"setting":[104],"stage":[106],"for":[107],"an":[111],"innovative":[112],"platform.":[113],"Due":[114],"its":[116],"power":[117],"handle":[119],"information":[120],"multiple":[122,130],"views,":[123],"platform":[125],"is":[126],"termed":[127],"(DMC)":[132],"analysis.":[133],"Depending":[134],"on":[135],"nature":[136],"data":[139],"sources":[140],"work":[142],"DMC":[144],"two":[146],"distinct":[147],"implementations,":[148],"one":[149],"perceptron-style":[152],"NN":[153,161],"(PNN),":[154],"other":[157],"convolution-style":[160],"(CNN).":[162],"Statistics":[163],"collected":[164],"experiments":[166],"numerous":[168],"analysis":[170],"recognition":[172],"benchmarks":[173],"evidently":[174],"show":[175],"that":[176],"not":[179],"only":[180],"generates":[181],"impressive":[182],"(sometimes":[183],"unprecedented)":[184],"performance":[185],"accuracies,":[186],"but":[187],"much":[188],"faster":[189],"speed":[191],"comparing":[192],"contemporary":[194],"DL-based":[195],"fusion":[196],"models.":[197],"Implementation":[198],"codes":[199],"will":[200],"be":[201],"available":[202],"online":[203],"soon.":[204]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-02-18T00:00:00"}
