{"id":"https://openalex.org/W4414856478","doi":"https://doi.org/10.1109/tmm.2025.3618576","title":"Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression","display_name":"Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414856478","doi":"https://doi.org/10.1109/tmm.2025.3618576"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3618576","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618576","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tmm.2025.3618576","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000482515","display_name":"Yi-Hsin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Yi-Hsin Li","raw_affiliation_strings":["Department of Telecommunication Systems, Technical University of Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunication Systems, Technical University of Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005859513","display_name":"Sebastian Knorr","orcid":"https://orcid.org/0000-0001-9745-8605"},"institutions":[{"id":"https://openalex.org/I205892228","display_name":"Berlin School of Economics and Law","ror":"https://ror.org/03rkmps36","country_code":"DE","type":"education","lineage":["https://openalex.org/I205892228"]},{"id":"https://openalex.org/I122228004","display_name":"HTW Berlin - University of Applied Sciences","ror":"https://ror.org/01xzwj424","country_code":"DE","type":"education","lineage":["https://openalex.org/I122228004"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Knorr","raw_affiliation_strings":["School of Computing, Communication and Business, Hochschule für Technik und Wirtschaft Berlin, Berlin, Germany","School of Computing, Communication and Business, Hochschule fur Technik und Wirtschaft Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"School of Computing, Communication and Business, Hochschule für Technik und Wirtschaft Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I122228004","https://openalex.org/I205892228"]},{"raw_affiliation_string":"School of Computing, Communication and Business, Hochschule fur Technik und Wirtschaft Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I122228004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061234993","display_name":"M\u00e5rten Sj\u00f6str\u00f6m","orcid":"https://orcid.org/0000-0003-3751-6089"},"institutions":[{"id":"https://openalex.org/I56475706","display_name":"Mid Sweden University","ror":"https://ror.org/019k1pd13","country_code":"SE","type":"education","lineage":["https://openalex.org/I56475706"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"M\u00e5rten Sj\u00f6str\u00f6m","raw_affiliation_strings":["Department of Computer and Electrical Engineering, Mid Sweden University, Sundsvall, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Electrical Engineering, Mid Sweden University, Sundsvall, Sweden","institution_ids":["https://openalex.org/I56475706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113970295","display_name":"Thomas Sikora","orcid":null},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Sikora","raw_affiliation_strings":["Department of Telecommunication Systems, Technical University of Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunication Systems, Technical University of Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000482515"],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32828893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"9802","last_page":"9817"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.7271000146865845,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.7271000146865845,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.6794999837875366,"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/T10057","display_name":"Face and Expression Recognition","score":0.6761000156402588,"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/initialization","display_name":"Initialization","score":0.935699999332428},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7350000143051147},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.49810001254081726},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.46810001134872437},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4043999910354614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3804999887943268},{"id":"https://openalex.org/keywords/kernel-regression","display_name":"Kernel regression","score":0.3643999993801117},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3546999990940094}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.935699999332428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7641000151634216},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7350000143051147},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4595000147819519},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4104999899864197},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4043999910354614},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C200695384","wikidata":"https://www.wikidata.org/wiki/Q1739319","display_name":"Kernel regression","level":3,"score":0.3643999993801117},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3546999990940094},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.35359999537467957},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.3203999996185303},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2890999913215637},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2678000032901764}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmm.2025.3618576","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618576","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:DiVA.org:miun-54545","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-54545","pdf_url":null,"source":{"id":"https://openalex.org/S4306402314","display_name":"Publications (Mid Sweden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56475706","host_organization_name":"Mid Sweden University","host_organization_lineage":["https://openalex.org/I56475706"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1109/tmm.2025.3618576","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618576","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Kernel":[0],"image":[1,10,14,79,128],"regression":[2,129],"methods":[3,29,165],"have":[4],"demonstrated":[5],"excellent":[6],"efficiency":[7],"in":[8,95,119,135],"various":[9],"processing":[11],"tasks,":[12],"including":[13],"and":[15,21,64,88,99,125,138,147],"light-field":[16],"compression,":[17],"Gaussian":[18],"Splatting,":[19],"denoising":[20],"super-resolution.":[22],"The":[23,71,81,103,152],"estimation":[24],"of":[25,84,122,189],"parameters":[26,90,176],"for":[27,42,57,117],"these":[28],"commonly":[30],"employs":[31],"gradient":[32],"descent":[33],"iterative":[34,97,120],"optimization,":[35],"which":[36],"poses":[37],"a":[38,50,113],"significant":[39,133],"computational":[40],"burden":[41],"many":[43],"applications.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48],"introduce":[49],"novel":[51,72],"adaptive":[52],"segmentation-based":[53,149],"initialization":[54,73,150,154,164,204],"method":[55,74,155,199],"targeted":[56],"optimizing":[58],"Steered-Mixture-of":[59],"Experts":[60],"(SMoE)":[61],"gating":[62],"networks":[63,67],"RadialBasis-Function":[65],"(RBF)":[66],"with":[68,203],"steering":[69,89],"kernels.":[70],"allocates":[75],"kernels":[76],"into":[77,112],"pre-calculated":[78],"segments.":[80],"optimal":[82],"number":[83],"kernels,":[85],"kernel":[86,100,104,127,157],"positions,":[87],"are":[91],"derived":[92],"per":[93],"segment":[94],"an":[96],"optimization":[98,121],"sparsification":[101],"procedure.":[102],"information":[105],"from":[106],"local":[107],"segments":[108],"is":[109,183],"then":[110],"transferred":[111],"global":[114],"initialization,":[115],"ready":[116],"use":[118],"SMoE,":[123],"RBF,":[124],"related":[126],"methods.":[130,151,196],"Results":[131],"demonstrate":[132],"improvements":[134],"both":[136],"objective":[137],"subjective":[139],"quality":[140],"compared":[141,161,193,211],"to":[142,162,178,191,194,212],"regular":[143],"grid,":[144],"K-Means,":[145],"deeplearning-based,":[146],"previous":[148],"proposed":[153],"reduces":[156],"usage":[158],"by":[159,173],"70%":[160],"other":[163],"while":[166],"maintaining":[167],"the":[168,198],"same":[169],"reconstruction":[170],"quality.":[171],"Furthermore,":[172],"generating":[174],"initial":[175],"closer":[177],"optimized":[179],"results,":[180],"convergence":[181],"time":[182,205],"reduced,":[184],"achieving":[185],"overall":[186],"runtime":[187],"savings":[188],"up":[190],"50%":[192],"prior":[195],"Additionally,":[197],"supports":[200],"parallel":[201],"computation,":[202],"halved":[206],"when":[207],"using":[208],"four":[209],"GPUs":[210],"one":[213]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}