{"id":"https://openalex.org/W7225313129","doi":"https://doi.org/10.3390/math14214049","title":"Low-Rank CP Tensor Decomposition for Lightweight Image Super-Resolution","display_name":"Low-Rank CP Tensor Decomposition for Lightweight Image Super-Resolution","publication_year":2026,"publication_date":"2026-11-05","ids":{"openalex":"https://openalex.org/W7225313129","doi":"https://doi.org/10.3390/math14214049"},"language":"en","primary_location":{"id":"doi:10.3390/math14214049","doi":"https://doi.org/10.3390/math14214049","is_oa":true,"landing_page_url":"https://doi.org/10.3390/math14214049","pdf_url":null,"source":{"id":"https://openalex.org/S4210192031","display_name":"Mathematics","issn_l":"2227-7390","issn":["2227-7390"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/math14214049","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114008096","display_name":"Huan Guo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162809","display_name":"Kashi University","ror":"https://ror.org/055a4rj94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162809"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Guo","raw_affiliation_strings":["College of Mathematics and Statistics, Kashi University, Kashi 844000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Kashi University, Kashi 844000, China","institution_ids":["https://openalex.org/I4210162809"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059394598","display_name":"Yuekai Liu","orcid":"https://orcid.org/0000-0002-3851-9487","observed_orcids":["https://orcid.org/0000-0002-3851-9487"]},"institutions":[{"id":"https://openalex.org/I4210162809","display_name":"Kashi University","ror":"https://ror.org/055a4rj94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162809"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuekai Liu","raw_affiliation_strings":["College of Mathematics and Statistics, Kashi University, Kashi 844000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Kashi University, Kashi 844000, China","institution_ids":["https://openalex.org/I4210162809"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022239704","display_name":"Shirong Li","orcid":"https://orcid.org/0009-0009-5191-6055","observed_orcids":["https://orcid.org/0009-0009-5191-6055"]},"institutions":[{"id":"https://openalex.org/I4210162809","display_name":"Kashi University","ror":"https://ror.org/055a4rj94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162809"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shirong Li","raw_affiliation_strings":["College of Mathematics and Statistics, Kashi University, Kashi 844000, China"],"raw_orcid":"https://orcid.org/0009-0009-5191-6055","affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Kashi University, Kashi 844000, China","institution_ids":["https://openalex.org/I4210162809"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022239704"],"corresponding_institution_ids":["https://openalex.org/I4210162809"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"21","first_page":"4049","last_page":"4049"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.7178000211715698,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.7178000211715698,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1273999959230423,"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/T12303","display_name":"Tensor decomposition and applications","score":0.10189999639987946,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/single-image-super-resolution","display_name":"single image super-resolution","score":0.9430000185966492},{"id":"https://openalex.org/keywords/lightweight-neural-networks","display_name":"lightweight neural networks","score":0.640999972820282},{"id":"https://openalex.org/keywords/edge-deployment","display_name":"edge deployment","score":0.5049999952316284},{"id":"https://openalex.org/keywords/alternating-direction-method-of-multipliers","display_name":"alternating direction method of multipliers","score":0.722000002861023},{"id":"https://openalex.org/keywords/proximal-gradient-descent","display_name":"proximal gradient descent","score":0.7760000228881836},{"id":"https://openalex.org/keywords/parameter-efficiency","display_name":"parameter efficiency","score":0.5189999938011169},{"id":"https://openalex.org/keywords/model-compression","display_name":"model compression","score":0.4300000071525574}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6007000207901001},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5845999717712402},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5105999708175659},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48590001463890076},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4681999981403351},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.460999995470047},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.44940000772476196},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.37689998745918274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C42704193","wikidata":"https://www.wikidata.org/wiki/Q7851097","display_name":"Tucker decomposition","level":4,"score":0.36090001463890076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3197999894618988},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2985000014305115},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.25699999928474426},{"id":"https://openalex.org/C51255310","wikidata":"https://www.wikidata.org/wiki/Q1163016","display_name":"Tensor product","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/math14214049","doi":"https://doi.org/10.3390/math14214049","is_oa":true,"landing_page_url":"https://doi.org/10.3390/math14214049","pdf_url":null,"source":{"id":"https://openalex.org/S4210192031","display_name":"Mathematics","issn_l":"2227-7390","issn":["2227-7390"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/math14214049","doi":"https://doi.org/10.3390/math14214049","is_oa":true,"landing_page_url":"https://doi.org/10.3390/math14214049","pdf_url":null,"source":{"id":"https://openalex.org/S4210192031","display_name":"Mathematics","issn_l":"2227-7390","issn":["2227-7390"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320328897","display_name":"Science and Technology Department of Xinjiang Uyghur Autonomous Region","ror":"https://ror.org/02vtvez67"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W2024165284","https://openalex.org/W2242218935","https://openalex.org/W2503339013","https://openalex.org/W2508457857","https://openalex.org/W2735224642","https://openalex.org/W2790610275","https://openalex.org/W2976718572","https://openalex.org/W3048878373","https://openalex.org/W3133531783","https://openalex.org/W3133953507","https://openalex.org/W4206344569","https://openalex.org/W4214537513","https://openalex.org/W4225576932","https://openalex.org/W4285188871","https://openalex.org/W4385151994","https://openalex.org/W4385815543","https://openalex.org/W4386525006","https://openalex.org/W4386835620","https://openalex.org/W4388756711","https://openalex.org/W4390871820","https://openalex.org/W4391753772","https://openalex.org/W4400700517","https://openalex.org/W4403863649","https://openalex.org/W4408974286","https://openalex.org/W4410013586","https://openalex.org/W4413751552","https://openalex.org/W4416509986"],"related_works":["https://openalex.org/W4417002534","https://openalex.org/W3210033632","https://openalex.org/W3034873840","https://openalex.org/W4400034427","https://openalex.org/W7164808284","https://openalex.org/W4226369573","https://openalex.org/W3118939638","https://openalex.org/W7213436512","https://openalex.org/W2181101938","https://openalex.org/W4411086371"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1,77],"neural":[2],"networks":[3],"have":[4],"substantially":[5],"advanced":[6],"single-image":[7],"super-resolution,":[8],"or":[9,31],"SR,":[10],"but":[11],"their":[12],"high":[13],"parameter":[14,138],"counts":[15],"and":[16,60,126,140,150,158,238],"computational":[17],"redundancy":[18],"hinder":[19],"deployment":[20],"on":[21,89,154,184],"resource-constrained":[22],"edge":[23],"devices.":[24],"Most":[25],"existing":[26],"compression":[27,48],"methods":[28],"apply":[29],"pruning":[30],"low-rank":[32,85],"truncation":[33],"as":[34,103],"a":[35,90,104,109,113,118,166,174,191,195,202,221,236],"post":[36],"hoc":[37],"step":[38],"after":[39,96],"training.":[40],"This":[41],"\u201ctrain-then-compress\u201d":[42],"pipeline":[43],"is":[44,235],"reported":[45],"in":[46,245],"the":[47,52,56,76,100,124,144,162,206,212,246],"literature":[49],"to":[50,61,65,194,201,217,241],"disrupt":[51],"spectral":[53],"coherence":[54],"of":[55,112,137,146,211,224],"learned":[57],"feature":[58],"manifold":[59,92],"require":[62],"costly":[63],"fine-tuning":[64],"restore":[66],"fidelity.":[67],"We":[68,98],"study":[69],"an":[70],"alternative,":[71],"training-time":[72,232],"approach":[73],"that":[74,161,231],"re-parameterizes":[75],"kernel":[78],"with":[79,173],"CANDECOMP/PARAFAC":[80],"(CP)":[81],"decomposition":[82,234],"into":[83],"three":[84],"sublayers,":[86],"optimizing":[87],"directly":[88],"rank-constrained":[91],"rather":[93,107],"than":[94,108],"compressing":[95],"convergence.":[97],"interpret":[99],"forward":[101],"pass":[102],"heuristic":[105],"realization,":[106],"formal":[110],"equivalence,":[111],"proximal":[114],"gradient-descent\u2013ADMM":[115],"update":[116],"for":[117],"tensor":[119],"nuclear-norm-regularized":[120],"problem,":[121],"which":[122],"motivates":[123],"design":[125],"its":[127],"hyperparameters":[128],"without":[129],"invoking":[130],"expensive":[131],"singular":[132],"value":[133],"decompositions.":[134,152],"An":[135],"analysis":[136],"complexity":[139],"gradient":[141],"flow":[142],"justifies":[143],"choice":[145],"CP":[147,163,233],"over":[148],"Tucker":[149],"tensor-train":[151],"Experiments":[153],"DIV2K,":[155],"Kodak24,":[156],"BSD100,":[157],"Set12":[159],"show":[160],"module":[164,208],"yields":[165],"0.11":[167],"M-parameter":[168],"lightweight":[169],"model":[170],"at":[171,220],"parity":[172],"same-budget":[175],"reduced":[176],"residual":[177,198],"baseline":[178],"(at":[179],"most":[180],"0.15":[181],"dB":[182],"difference":[183],"every":[185],"test":[186],"set),":[187],"sacrificing":[188],"roughly":[189],"half":[190],"decibel":[192],"relative":[193],"5.2\u00d7":[196],"larger":[197],"baseline.":[199],"Applied":[200],"large-capacity":[203],"SR":[204,243],"backbone,":[205],"same":[207],"removes":[209],"76.7%":[210],"parameters,":[213],"from":[214],"13.28":[215],"M":[216],"3.09":[218],"M,":[219],"PSNR":[222],"cost":[223],"only":[225],"0.11\u20130.20":[226],"dB.":[227],"These":[228],"results":[229],"indicate":[230],"simple":[237],"parameter-efficient":[239],"route":[240],"compact":[242],"models":[244],"extreme-compression":[247],"regime.":[248]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-11-06T00:00:00"}
