{"id":"https://openalex.org/W4385341218","doi":"https://doi.org/10.3233/jifs-230569","title":"Deep pyramidal residual networks with inception sub-structure in image classification","display_name":"Deep pyramidal residual networks with inception sub-structure in image classification","publication_year":2023,"publication_date":"2023-07-28","ids":{"openalex":"https://openalex.org/W4385341218","doi":"https://doi.org/10.3233/jifs-230569"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-230569","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-230569","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","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/A5100746419","display_name":"Fei Xu","orcid":"https://orcid.org/0000-0001-9501-5085"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fei Xu","raw_affiliation_strings":["Department of Applied Mathematics, Northeast Agricultural University, Harbin, P R China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Northeast Agricultural University, Harbin, P R China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396004","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0002-2801-4012"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wang","raw_affiliation_strings":["Department of Applied Mathematics, Northeast Agricultural University, Harbin, P R China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Northeast Agricultural University, Harbin, P R China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102117066","display_name":"Huimin Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huimin Xu","raw_affiliation_strings":["Public Teaching Department of Mathematics, Northeast Agricultural University, Harbin, P R China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Public Teaching Department of Mathematics, Northeast Agricultural University, Harbin, P R China","institution_ids":["https://openalex.org/I169572211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100746419"],"corresponding_institution_ids":["https://openalex.org/I169572211"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07488862,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"4","first_page":"5885","last_page":"5906"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9962000250816345,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9962000250816345,"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":0.9922999739646912,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7536019086837769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6970251798629761},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.647590160369873},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5928053855895996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5743173360824585},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5625295042991638},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5586729049682617},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47814831137657166},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4581086337566376},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41881412267684937},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.351046621799469},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3213127553462982}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7536019086837769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6970251798629761},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.647590160369873},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5928053855895996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5743173360824585},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5625295042991638},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5586729049682617},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47814831137657166},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4581086337566376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41881412267684937},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.351046621799469},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3213127553462982},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-230569","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-230569","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2911810010","https://openalex.org/W2964137095","https://openalex.org/W3009225866","https://openalex.org/W4293235225","https://openalex.org/W4319985874","https://openalex.org/W6713132643"],"related_works":["https://openalex.org/W4295815739","https://openalex.org/W2915512385","https://openalex.org/W2964954556","https://openalex.org/W3019910406","https://openalex.org/W2952813363","https://openalex.org/W4378678253","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W2972076240"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1,30],"neural":[2],"networks":[3,128],"(DCNNs)":[4],"have":[5],"shown":[6],"remarkable":[7],"performance":[8,136,154],"in":[9,13,41,58,80,152,251],"image":[10],"classification":[11],"tasks":[12],"recent":[14],"years.":[15],"In":[16,103,130,180],"the":[17,23,27,38,42,45,48,72,75,81,93,111,115,118,135,163,174,181,186,193,199,204,209,220,230],"network":[18,24,60,120,139,153,212,215,245],"structure":[19,113],"of":[20,29,47,67,77,117,137,183,196,217,223,241],"DPRN,":[21,168],"as":[22],"depth":[25,161,216],"increases,":[26],"number":[28,76],"kernels":[31,79],"also":[32,133],"increases":[33],"linearly":[34],"or":[35],"nonlinearly.":[36],"On":[37,71],"one":[39],"hand,":[40,74],"DPRN":[43,119,242],"block,":[44],"size":[46],"receptive":[49],"field":[50],"is":[51,122],"only":[52],"3":[53],"\u00d7":[54],"3,":[55],"which":[56,96,121,247],"results":[57,151,172,222],"insufficient":[59],"ability":[61],"to":[62,92,100,105,167,229],"extract":[63],"feature":[64],"map":[65],"information":[66],"different":[68],"filter":[69],"sizes.":[70],"other":[73],"convolution":[78,84],"second":[82],"1x1":[83],"will":[85],"be":[86],"multiplied":[87],"by":[88,124],"a":[89,159,214],"coefficient":[90],"relative":[91],"first":[94],"convolution,":[95],"can":[97],"cause":[98],"overfitting":[99],"some":[101,150],"extent.":[102],"order":[104],"overcome":[106],"these":[107],"weaknesses,":[108],"we":[109,132],"introduce":[110],"inception-like":[112],"on":[114,173,198,203],"basis":[116],"called":[123],"pyramid":[125],"inceptional":[126],"residual":[127],"(PIRN).":[129],"addition,":[131],"discuss":[134],"PIRN":[138,164,169,188,211],"with":[140,189,213,243],"squeeze":[141],"and":[142,146,177,206,225],"excitation":[143],"(SE)":[144],"mechanism":[145,191],"regularization":[147],"term.":[148],"Furthermore,":[149],"are":[155],"discussed":[156],"when":[157],"adding":[158],"stochastic":[160],"networkto":[162],"model.":[165],"Compared":[166],"achieved":[170,236],"better":[171,237],"CIFAR10,":[175],"CIFAR100,":[176],"Mini-ImageNet":[178,207],"datasets.":[179],"case":[182],"using":[184],"zero-padding,":[185],"multiplicative":[187],"SE":[190],"achieves":[192,219],"best":[194,221],"result":[195],"95.01%":[197],"CIFAR10":[200],"dataset.":[201],"Meanwhile,":[202],"CIFAR100":[205],"datasets,":[208],"additive":[210],"92":[218],"76.06%":[224],"65.86%,":[226],"respectively.":[227],"According":[228],"experimental":[231],"results,":[232],"our":[233],"method":[234],"has":[235],"accuray":[238],"than":[239],"that":[240],"same":[244],"settings":[246],"demonstrate":[248],"its":[249],"effectiveness":[250],"generalization":[252],"ability.":[253]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
