{"id":"https://openalex.org/W7125958063","doi":"https://doi.org/10.1109/smc58881.2025.11342863","title":"Best Initialization Vectors: Image Dimensionality Reduction and Linear Feature Analysis","display_name":"Best Initialization Vectors: Image Dimensionality Reduction and Linear Feature Analysis","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125958063","doi":"https://doi.org/10.1109/smc58881.2025.11342863"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342863","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 Systems, Man, and Cybernetics (SMC)","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/A5124149202","display_name":"Yichen Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yichen Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124098086","display_name":"Hongxu Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongxu Hou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124064609","display_name":"Wei Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5124149202"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87249177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2913","last_page":"2918"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.2574000060558319,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.2574000060558319,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.09669999778270721,"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/T10057","display_name":"Face and Expression Recognition","score":0.08820000290870667,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7630000114440918},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7595000267028809},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6729000210762024},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6409000158309937},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5805000066757202},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5224999785423279},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.44429999589920044},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.44029998779296875}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7630000114440918},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7595000267028809},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6729000210762024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539000272750854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6496999859809875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6409000158309937},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5805000066757202},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5224999785423279},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.44429999589920044},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4146000146865845},{"id":"https://openalex.org/C165443888","wikidata":"https://www.wikidata.org/wiki/Q1482183","display_name":"Transformation matrix","level":3,"score":0.414000004529953},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.3921999931335449},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38499999046325684},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.3603000044822693},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.3319999873638153},{"id":"https://openalex.org/C49766605","wikidata":"https://www.wikidata.org/wiki/Q207643","display_name":"Linear map","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2896000146865845},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26429998874664307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2621000111103058},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342863","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 Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1602112707","https://openalex.org/W1994005439","https://openalex.org/W2011174137","https://openalex.org/W2053186076","https://openalex.org/W2128728535","https://openalex.org/W2194775991","https://openalex.org/W2964821232","https://openalex.org/W3147852756","https://openalex.org/W3212386989","https://openalex.org/W4229706427","https://openalex.org/W4390872911","https://openalex.org/W4391070429","https://openalex.org/W4391420769","https://openalex.org/W4392903361","https://openalex.org/W4400111461","https://openalex.org/W4400370893","https://openalex.org/W4400491051"],"related_works":[],"abstract_inverted_index":{"In":[0],"high-dimensional":[1,96],"feature":[2,33,110],"extraction":[3,34],"tasks,":[4],"probabilistic":[5],"methods":[6,18],"integrated":[7],"with":[8,123],"machine":[9],"learning":[10],"processes":[11],"have":[12],"become":[13],"mainstream.":[14],"However,":[15],"while":[16,120],"these":[17],"help":[19],"alleviate":[20],"model":[21],"complexity,":[22],"they":[23],"often":[24],"introduce":[25],"additional":[26],"training":[27],"burdens.":[28],"To":[29,127],"simultaneously":[30],"achieve":[31],"effective":[32],"and":[35,83],"reduced":[36],"computational":[37],"cost,":[38],"we":[39,66,131],"propose":[40],"a":[41,75,81],"novel":[42],"linear":[43],"dimensionality":[44,62,93,149],"reduction":[45,94,150],"method":[46,142],"called":[47],"Best":[48],"Initialization":[49],"Vector":[50],"(BIV),":[51],"which":[52],"leverages":[53],"the":[54,61,68,78,103,116],"principle":[55],"of":[56,63,70,95,105,118],"basis":[57,85],"transformation":[58,86],"to":[59,87],"reduce":[60],"images.":[64],"Specifically,":[65],"exploit":[67],"properties":[69],"matrix":[71],"space":[72,79],"by":[73],"initializing":[74],"vector":[76,100],"within":[77],"as":[80],"parameter,":[82],"applying":[84],"perform":[88],"computations.":[89],"This":[90],"enables":[91],"extreme":[92,148],"image":[97,109],"data":[98],"into":[99],"representations,":[101],"allowing":[102],"use":[104],"NLP":[106,125],"models":[107],"for":[108],"extraction.":[111],"Our":[112],"approach":[113],"significantly":[114],"reduces":[115],"number":[117],"parameters":[119],"maintaining":[121],"compatibility":[122],"various":[124],"modules.":[126],"evaluate":[128],"its":[129],"effectiveness,":[130],"conducted":[132],"experiments":[133],"on":[134],"multiple":[135],"datasets.":[136],"The":[137],"results":[138],"demonstrate":[139],"that":[140],"our":[141],"outperforms":[143],"existing":[144],"mainstream":[145],"approaches":[146],"under":[147],"scenarios.":[151]},"counts_by_year":[],"updated_date":"2026-01-29T23:17:01.242718","created_date":"2026-01-29T00:00:00"}