{"id":"https://openalex.org/W4402351749","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650281","title":"AdaFSNet: Time Series Classification Based on Convolutional Network with a Adaptive and Effective Kernel Size Configuration","display_name":"AdaFSNet: Time Series Classification Based on Convolutional Network with a Adaptive and Effective Kernel Size Configuration","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351749","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650281"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5057219846","display_name":"Haoxiao Wang","orcid":"https://orcid.org/0009-0000-4252-4353"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haoxiao Wang","raw_affiliation_strings":["Tianjin University of Technology,School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,School of Computer Science and Engineering","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061202217","display_name":"Bo Peng","orcid":"https://orcid.org/0000-0002-6616-453X"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Peng","raw_affiliation_strings":["Tianjin University of Technology,School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,School of Computer Science and Engineering","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434758","display_name":"Jianhua Zhang","orcid":"https://orcid.org/0000-0001-7844-6035"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Zhang","raw_affiliation_strings":["Tianjin University of Technology,School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,School of Computer Science and Engineering","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100430968","display_name":"Cheng Xu","orcid":"https://orcid.org/0000-0001-8075-2867"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Cheng","raw_affiliation_strings":["Tianjin University of Technology,School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,School of Computer Science and Engineering","institution_ids":["https://openalex.org/I136765683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057219846"],"corresponding_institution_ids":["https://openalex.org/I136765683"],"apc_list":null,"apc_paid":null,"fwci":1.1251,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77636792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9934999942779541,"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/T11309","display_name":"Music and Audio Processing","score":0.9599999785423279,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7141448855400085},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6764832139015198},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6702651977539062},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4828920364379883},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4603436291217804},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4567715525627136},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37647202610969543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2847776412963867},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19595593214035034},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.05374652147293091}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7141448855400085},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6764832139015198},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6702651977539062},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4828920364379883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4603436291217804},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4567715525627136},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37647202610969543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2847776412963867},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19595593214035034},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.05374652147293091},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W585336894","https://openalex.org/W1522301498","https://openalex.org/W1968354112","https://openalex.org/W1984674851","https://openalex.org/W2024300411","https://openalex.org/W2070808135","https://openalex.org/W2081028405","https://openalex.org/W2177178155","https://openalex.org/W2306394264","https://openalex.org/W2551393996","https://openalex.org/W2555077524","https://openalex.org/W2752782242","https://openalex.org/W2754051771","https://openalex.org/W2757143157","https://openalex.org/W2783323081","https://openalex.org/W2798297823","https://openalex.org/W2802922942","https://openalex.org/W2892035503","https://openalex.org/W2947644971","https://openalex.org/W2963446712","https://openalex.org/W2963828549","https://openalex.org/W2964081807","https://openalex.org/W2964140963","https://openalex.org/W2964350391","https://openalex.org/W2965157938","https://openalex.org/W2972810968","https://openalex.org/W2981830988","https://openalex.org/W2982438846","https://openalex.org/W3042807565","https://openalex.org/W3083891030","https://openalex.org/W3094085017","https://openalex.org/W3096809883","https://openalex.org/W4287865152","https://openalex.org/W4289360400","https://openalex.org/W4388074308","https://openalex.org/W6631190155","https://openalex.org/W6685675117","https://openalex.org/W6698169118","https://openalex.org/W6718764840","https://openalex.org/W6744702893","https://openalex.org/W6745499552","https://openalex.org/W6755529311","https://openalex.org/W6762947928","https://openalex.org/W6840726259","https://openalex.org/W6870688871"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W1919101720","https://openalex.org/W2181413294","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Time":[0],"series":[1,51,89,126,168,191],"classification":[2,179,192],"is":[3],"one":[4],"of":[5,38,52,87,104,148,178],"the":[6,36,40,85,110,124,146,149,157,182],"most":[7],"critical":[8],"and":[9,20,28,63,76,159,165,186],"challenging":[10],"problems":[11],"in":[12,17,176,188],"data":[13],"mining,":[14],"existing":[15],"widely":[16],"various":[18,115],"fields":[19],"holding":[21],"significant":[22],"research":[23,27],"importance.":[24],"Despite":[25],"extensive":[26],"notable":[29],"achievements":[30],"with":[31],"successful":[32],"real-world":[33],"applications,":[34],"addressing":[35],"challenge":[37],"capturing":[39],"appropriate":[41],"receptive":[42],"field":[43],"(RF)":[44],"size":[45,113],"from":[46],"one-dimensional":[47,164],"or":[48],"multi-dimensional":[49,166],"time":[50,88,125,167,190],"varying":[53],"lengths":[54],"remains":[55],"a":[56,102,131,140],"persistent":[57],"issue,":[58],"which":[59,134,162],"greatly":[60],"impacts":[61],"performance":[62],"varies":[64],"considerably":[65],"across":[66],"different":[67],"datasets.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72],"propose":[73],"an":[74],"Adaptive":[75],"Effective":[77],"Full-Scope":[78],"Convolutional":[79],"Neural":[80],"Network":[81],"(AdaFSNet)":[82],"to":[83,123],"enhance":[84],"accuracy":[86],"classification.":[90],"This":[91],"network":[92],"includes":[93],"two":[94],"Dense":[95],"Blocks.":[96],"Particularly,":[97],"it":[98],"can":[99,135],"dynamically":[100],"choose":[101],"range":[103],"kernel":[105],"sizes":[106],"that":[107],"effectively":[108],"encompass":[109],"optimal":[111],"RF":[112],"for":[114],"datasets":[116],"by":[117],"incorporating":[118],"multiple":[119],"prime":[120],"numbers":[121],"corresponding":[122],"length.":[127],"We":[128],"also":[129],"design":[130],"TargetDrop":[132],"block,":[133],"reduce":[136],"redundancy":[137],"while":[138],"extracting":[139],"more":[141],"effective":[142],"RF.":[143],"To":[144],"assess":[145],"effectiveness":[147,187],"AdaFSNet":[150,183],"network,":[151],"comprehensive":[152],"experiments":[153],"were":[154],"conducted":[155],"using":[156],"UCR":[158],"UEA":[160],"datasets,":[161],"include":[163],"data,":[169],"respectively.":[170],"Our":[171],"model":[172],"surpassed":[173],"baseline":[174],"models":[175],"terms":[177],"accuracy,":[180],"underscoring":[181],"network\u2019s":[184],"efficiency":[185],"handling":[189],"tasks.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}