{"id":"https://openalex.org/W3201185393","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533788","title":"Adaptive Dila-DenseNet for Image based Time Series Classification in IoT","display_name":"Adaptive Dila-DenseNet for Image based Time Series Classification in IoT","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201185393","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533788","mag":"3201185393"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5101243049","display_name":"Qiao Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiao Jiang","raw_affiliation_strings":["Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450332","display_name":"Shuo Zhang","orcid":"https://orcid.org/0000-0001-5197-6028"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Zhang","raw_affiliation_strings":["Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031618552","display_name":"Jiayuan Chen","orcid":"https://orcid.org/0000-0002-2581-951X"},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayuan Chen","raw_affiliation_strings":["Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358416","display_name":"Xiaofei Chen","orcid":"https://orcid.org/0000-0002-0950-8121"},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Chen","raw_affiliation_strings":["Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006819425","display_name":"Hejiao Huang","orcid":"https://orcid.org/0000-0002-2030-957X"},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hejiao Huang","raw_affiliation_strings":["Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103228633","display_name":"Chonglin Gu","orcid":"https://orcid.org/0000-0002-9656-6265"},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chonglin Gu","raw_affiliation_strings":["Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (ShenZhen),The Department of Computer Science and Technology,ShenZhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101243049"],"corresponding_institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12325896,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"abs 1811 75","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":0.9959999918937683,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7681201696395874},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5949695706367493},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5787060260772705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5737735629081726},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5568474531173706},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5396236777305603},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4949776530265808},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4614950120449066},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4566539525985718},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44472020864486694},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4397757947444916},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.41380494832992554},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33593204617500305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2465103268623352},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12334075570106506}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7681201696395874},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5949695706367493},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5787060260772705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5737735629081726},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5568474531173706},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5396236777305603},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4949776530265808},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4614950120449066},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4566539525985718},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44472020864486694},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4397757947444916},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41380494832992554},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33593204617500305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2465103268623352},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12334075570106506},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/ijcnn52387.2021.9533788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W119403003","https://openalex.org/W1966554111","https://openalex.org/W2035104901","https://openalex.org/W2054326990","https://openalex.org/W2101713460","https://openalex.org/W2105759654","https://openalex.org/W2143267104","https://openalex.org/W2144380653","https://openalex.org/W2163382420","https://openalex.org/W2531409750","https://openalex.org/W2551393996","https://openalex.org/W2592939477","https://openalex.org/W2598525681","https://openalex.org/W2746535784","https://openalex.org/W2754051771","https://openalex.org/W2763079654","https://openalex.org/W2783323081","https://openalex.org/W2786161686","https://openalex.org/W2888477829","https://openalex.org/W2890443177","https://openalex.org/W2892035503","https://openalex.org/W2898647012","https://openalex.org/W2910862205","https://openalex.org/W2949855236","https://openalex.org/W2962850830","https://openalex.org/W2963446712","https://openalex.org/W2963840672","https://openalex.org/W2963866024","https://openalex.org/W2964010366","https://openalex.org/W2978259066","https://openalex.org/W2988244882","https://openalex.org/W3093525187","https://openalex.org/W3120740533","https://openalex.org/W4289360400","https://openalex.org/W6604801135","https://openalex.org/W6604828220","https://openalex.org/W6675357634","https://openalex.org/W6689521540","https://openalex.org/W6696085341","https://openalex.org/W6725739302","https://openalex.org/W6728184133","https://openalex.org/W6755529311","https://openalex.org/W6768598080"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175"],"abstract_inverted_index":{"As":[0],"a":[1,16],"critical":[2],"problem":[3],"in":[4,25,42,49,143,158,203],"time":[5,9,23,56,63,89],"series":[6,10,64],"data":[7],"mining,":[8],"classification":[11],"(TSC)":[12],"has":[13],"always":[14],"been":[15],"challenging":[17],"task":[18],"for":[19,108,119,150],"high-dimensional":[20],"and":[21,72,84,103,122,128,195],"high-frequency":[22],"sequences":[24],"internet":[26],"of":[27,55,87,155],"things":[28],"(IoT),":[29],"Recently,":[30],"convolutional":[31],"neural":[32],"networks":[33],"(CNNs)":[34],"have":[35],"exhibited":[36],"great":[37],"superiority":[38],"on":[39,184],"TSC":[40],"tasks":[41],"deep":[43,160,200],"learning":[44,161,201],"models,":[45],"but":[46],"not":[47],"effective":[48],"capturing":[50],"the":[51,81,134,140,179,198],"long-term":[52],"temporal":[53,82],"dependency":[54,83],"series.":[57],"In":[58,110],"this":[59,174],"paper,":[60],"we":[61,112,138],"transform":[62],"into":[65],"GM-images":[66,107,156],"by":[67,133],"Gramian":[68],"Angular":[69],"Field":[70,75],"(GAF)":[71],"Markov":[73],"Transition":[74],"(MTF),":[76],"which":[77],"can":[78,172],"well":[79],"preserve":[80,146],"transition":[85],"statistics":[86],"raw":[88],"series,":[90],"respectively.":[91],"We":[92],"further":[93],"propose":[94],"an":[95,114],"efficient":[96],"Adaptive":[97],"Dila-DenseNet":[98],"(ADDN)":[99],"to":[100,145,165],"extract":[101],"various":[102],"discernable":[104],"patterns":[105],"from":[106,126],"TSC.":[109],"ADDN,":[111],"devise":[113],"adaptive":[115],"feature":[116],"aggregation":[117],"method":[118],"combining":[120],"static":[121],"dynamic":[123],"information":[124,149],"flexibly":[125],"GAF":[127],"MTF":[129],"representations.":[130],"Moreover,":[131],"inspired":[132],"dilated":[135],"residual":[136],"networks,":[137],"design":[139],"Dila-Dense":[141,170],"block":[142,171],"ADDN":[144],"local":[147],"spatial":[148],"GM-images.":[151],"The":[152],"significant":[153],"decrease":[154],"resolution":[157,175],"common":[159],"models":[162],"may":[163],"lead":[164],"performance":[166],"degradation.":[167],"Nevertheless,":[168],"our":[169,190],"address":[173],"issue":[176],"without":[177],"decreasing":[178],"receptive":[180],"field.":[181],"Experiments":[182],"evaluated":[183],"24":[185],"benchmark":[186],"datasets":[187],"demonstrate":[188],"that":[189],"approach":[191],"shows":[192],"greater":[193],"efficiency":[194],"efficacy":[196],"over":[197],"compared":[199],"baselines,":[202],"IoT.":[204]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}