{"id":"https://openalex.org/W4387405184","doi":"https://doi.org/10.1142/s0218126624501202","title":"Hybrid Deep Learning Model Based on Sparse Recurrent Architecture","display_name":"Hybrid Deep Learning Model Based on Sparse Recurrent Architecture","publication_year":2023,"publication_date":"2023-10-06","ids":{"openalex":"https://openalex.org/W4387405184","doi":"https://doi.org/10.1142/s0218126624501202"},"language":"en","primary_location":{"id":"doi:10.1142/s0218126624501202","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126624501202","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-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/A5080114976","display_name":"Yutao Wu","orcid":"https://orcid.org/0009-0009-1548-4996"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutao Wu","raw_affiliation_strings":["Institute for Future, School of Automation, Qingdao University, Qingdao, Shandong 266000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0009-1548-4996","affiliations":[{"raw_affiliation_string":"Institute for Future, School of Automation, Qingdao University, Qingdao, Shandong 266000, P. R. China","institution_ids":["https://openalex.org/I108688024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100343955","display_name":"Min Liu","orcid":"https://orcid.org/0009-0007-4100-1682"},"institutions":[{"id":"https://openalex.org/I31637741","display_name":"Inner Mongolia University of Science and Technology","ror":"https://ror.org/044rgx723","country_code":"CN","type":"education","lineage":["https://openalex.org/I31637741"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Liu","raw_affiliation_strings":["School of Economics and Management, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, P. R. China"],"raw_orcid":"https://orcid.org/0009-0007-4100-1682","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, P. R. China","institution_ids":["https://openalex.org/I31637741"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1632,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56583967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"33","issue":"07","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.453900009393692,"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":0.453900009393692,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7903151512145996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6535109281539917},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6497650742530823},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6485157012939453},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6100540161132812},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5359569191932678},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5149132013320923},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4944634437561035},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4897587299346924},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46265560388565063},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4118829369544983},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37520578503608704},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09421080350875854},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08223608136177063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7903151512145996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6535109281539917},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6497650742530823},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6485157012939453},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6100540161132812},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5359569191932678},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5149132013320923},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4944634437561035},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4897587299346924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46265560388565063},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4118829369544983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37520578503608704},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09421080350875854},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08223608136177063},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218126624501202","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126624501202","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1991539813","https://openalex.org/W2037227137","https://openalex.org/W2120907531","https://openalex.org/W2194775991","https://openalex.org/W2808133870","https://openalex.org/W2886851211","https://openalex.org/W2955305484","https://openalex.org/W2963125010","https://openalex.org/W2963446712","https://openalex.org/W2963918968","https://openalex.org/W2964081807","https://openalex.org/W2971724044","https://openalex.org/W2979040987","https://openalex.org/W2980186997","https://openalex.org/W2986195400","https://openalex.org/W3004543888","https://openalex.org/W3004619146","https://openalex.org/W3007031763","https://openalex.org/W3015735225","https://openalex.org/W3016954138","https://openalex.org/W3090234134","https://openalex.org/W3095508601","https://openalex.org/W3121852482","https://openalex.org/W3134772852","https://openalex.org/W3150224073","https://openalex.org/W3154435685","https://openalex.org/W3168997536","https://openalex.org/W3170841864","https://openalex.org/W3172752666","https://openalex.org/W3175645569","https://openalex.org/W3215511989","https://openalex.org/W4285247671","https://openalex.org/W4312959111"],"related_works":["https://openalex.org/W1663079876","https://openalex.org/W2069133146","https://openalex.org/W2017545316","https://openalex.org/W2100576949","https://openalex.org/W2159686533","https://openalex.org/W4242339654","https://openalex.org/W2349160795","https://openalex.org/W2100057527","https://openalex.org/W2809456908","https://openalex.org/W4205470293"],"abstract_inverted_index":{"Deep":[0],"neural":[1,55],"network":[2,56,74,84,88,120],"has":[3],"made":[4],"surprising":[5],"achievements":[6],"in":[7,18],"natural":[8],"language":[9],"processing,":[10],"image":[11],"pattern":[12],"classification":[13],"recognition,":[14],"and":[15,71,86,108,114,135,144],"other":[16],"domains":[17],"the":[19,36,61,68,73,77,82,87,97,118,126,129],"last":[20],"few":[21],"years.":[22],"It":[23],"is":[24,58,64,79,90,138],"still":[25],"tough":[26],"to":[27,29,66],"apply":[28],"hardware-constrained":[30],"or":[31],"mobile":[32],"equipment":[33],"because":[34],"of":[35,39,128],"huge":[37],"number":[38],"parameters,":[40],"high":[41],"storage":[42],"as":[43,45],"well":[44],"computing":[46],"costs.":[47],"In":[48],"this":[49],"paper,":[50],"a":[51],"new":[52],"sparse":[53,83,119],"iteration":[54],"architecture":[57,78],"proposed.":[59],"First,":[60],"pruning":[62],"method":[63],"used":[65],"compress":[67],"model":[69,101],"size":[70],"make":[72],"sparse.":[75],"Then":[76],"iterated":[80],"on":[81,105,111],"model,":[85],"performance":[89],"improved":[91,139],"without":[92],"adding":[93],"additional":[94],"parameters.":[95],"Finally,":[96],"hybrid":[98],"deep":[99],"learning":[100],"was":[102],"carried":[103],"out":[104],"CV":[106],"tasks":[107,110],"NLP":[109],"ANN,":[112],"CNN,":[113],"Transformer.":[115],"Compared":[116],"with":[117],"architecture,":[121],"we":[122],"finally":[123],"found":[124],"that":[125],"accuracy":[127],"MINST,":[130],"CIFAR10,":[131],"PASCAL":[132],"VOC":[133],"2012,":[134],"SQuAD":[136],"datasets":[137],"by":[140],"0.47%,":[141],"0.64%,":[142],"3.75%,":[143],"15.06%,":[145],"respectively.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}