{"id":"https://openalex.org/W4416788074","doi":"https://doi.org/10.3390/make7040155","title":"Time Series-to-Image Encoding for Classification Using Convolutional Neural Networks: A Novel and Robust Approach","display_name":"Time Series-to-Image Encoding for Classification Using Convolutional Neural Networks: A Novel and Robust Approach","publication_year":2025,"publication_date":"2025-11-28","ids":{"openalex":"https://openalex.org/W4416788074","doi":"https://doi.org/10.3390/make7040155"},"language":"en","primary_location":{"id":"doi:10.3390/make7040155","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7040155","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/make7040155","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113068636","display_name":"Hammoud Al Joumaa","orcid":null},"institutions":[{"id":"https://openalex.org/I102520234","display_name":"TH K\u00f6ln - University of Applied Sciences","ror":"https://ror.org/014nnvj65","country_code":"DE","type":"education","lineage":["https://openalex.org/I102520234"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hammoud Al Joumaa","raw_affiliation_strings":["Cologne Laboratory for Artificial Intelligence and Smart Automation (CAISA), Institute of Product Development and Engineering Design, Faculty of Process Engineering, Energy and Mechanical Systems, TH K\u00f6ln\u2014University of Applied Sciences, Betzdorfer Street 2, 50679 Cologne, Germany"],"affiliations":[{"raw_affiliation_string":"Cologne Laboratory for Artificial Intelligence and Smart Automation (CAISA), Institute of Product Development and Engineering Design, Faculty of Process Engineering, Energy and Mechanical Systems, TH K\u00f6ln\u2014University of Applied Sciences, Betzdorfer Street 2, 50679 Cologne, Germany","institution_ids":["https://openalex.org/I102520234"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081787337","display_name":"Loui Al-Shrouf","orcid":"https://orcid.org/0000-0002-1555-8715"},"institutions":[{"id":"https://openalex.org/I102520234","display_name":"TH K\u00f6ln - University of Applied Sciences","ror":"https://ror.org/014nnvj65","country_code":"DE","type":"education","lineage":["https://openalex.org/I102520234"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Loui Al-Shrouf","raw_affiliation_strings":["Cologne Laboratory for Artificial Intelligence and Smart Automation (CAISA), Institute of Product Development and Engineering Design, Faculty of Process Engineering, Energy and Mechanical Systems, TH K\u00f6ln\u2014University of Applied Sciences, Betzdorfer Street 2, 50679 Cologne, Germany"],"affiliations":[{"raw_affiliation_string":"Cologne Laboratory for Artificial Intelligence and Smart Automation (CAISA), Institute of Product Development and Engineering Design, Faculty of Process Engineering, Energy and Mechanical Systems, TH K\u00f6ln\u2014University of Applied Sciences, Betzdorfer Street 2, 50679 Cologne, Germany","institution_ids":["https://openalex.org/I102520234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051539079","display_name":"Mohieddine Jelali","orcid":"https://orcid.org/0000-0002-0347-9913"},"institutions":[{"id":"https://openalex.org/I102520234","display_name":"TH K\u00f6ln - University of Applied Sciences","ror":"https://ror.org/014nnvj65","country_code":"DE","type":"education","lineage":["https://openalex.org/I102520234"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Mohieddine Jelali","raw_affiliation_strings":["Cologne Laboratory for Artificial Intelligence and Smart Automation (CAISA), Institute of Product Development and Engineering Design, Faculty of Process Engineering, Energy and Mechanical Systems, TH K\u00f6ln\u2014University of Applied Sciences, Betzdorfer Street 2, 50679 Cologne, Germany"],"affiliations":[{"raw_affiliation_string":"Cologne Laboratory for Artificial Intelligence and Smart Automation (CAISA), Institute of Product Development and Engineering Design, Faculty of Process Engineering, Energy and Mechanical Systems, TH K\u00f6ln\u2014University of Applied Sciences, Betzdorfer Street 2, 50679 Cologne, Germany","institution_ids":["https://openalex.org/I102520234"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051539079","https://openalex.org/A5113068636"],"corresponding_institution_ids":["https://openalex.org/I102520234"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4768278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"4","first_page":"155","last_page":"155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.7091000080108643,"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":0.7091000080108643,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.031199999153614044,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.012400000356137753,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5681999921798706},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5217999815940857},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5138000249862671},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44290000200271606},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.43700000643730164},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4235999882221222},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.412200003862381},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4009000062942505},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7445999979972839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7128000259399414},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5681999921798706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5217999815940857},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5138000249862671},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.43700000643730164},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4235999882221222},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3499999940395355},{"id":"https://openalex.org/C77246614","wikidata":"https://www.wikidata.org/wiki/Q1409400","display_name":"Gramian matrix","level":3,"score":0.3224000036716461},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3158999979496002},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30169999599456787},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make7040155","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7040155","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:feadeda3071e45d58f18e0cd6d0e19f4","is_oa":true,"landing_page_url":"https://doaj.org/article/feadeda3071e45d58f18e0cd6d0e19f4","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 7, Iss 4, p 155 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make7040155","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7040155","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1976990135","https://openalex.org/W2006852365","https://openalex.org/W2095739681","https://openalex.org/W2099593264","https://openalex.org/W2101926813","https://openalex.org/W2106595237","https://openalex.org/W2112796928","https://openalex.org/W2122336162","https://openalex.org/W2299944668","https://openalex.org/W2404692435","https://openalex.org/W2762364541","https://openalex.org/W2764276316","https://openalex.org/W2892035503","https://openalex.org/W2892157245","https://openalex.org/W2919115771","https://openalex.org/W2962752580","https://openalex.org/W2968923792","https://openalex.org/W3023384820","https://openalex.org/W3038777551","https://openalex.org/W3082684473","https://openalex.org/W4210567336","https://openalex.org/W4225716729","https://openalex.org/W4306319588","https://openalex.org/W4316653939","https://openalex.org/W4319151686","https://openalex.org/W4321843574"],"related_works":[],"abstract_inverted_index":{"In":[0,72],"recent":[1],"decades,":[2],"data":[3,59,91,94,100,103],"collection":[4],"technologies":[5],"have":[6],"evolved":[7],"to":[8,36,62,66],"facilitate":[9],"the":[10,28,41,82,86,106,162,166,170,173,179,186],"monitoring":[11],"and":[12,17,53,69,131,142,169,181,199],"improvement":[13],"of":[14,30,43,49,88,110,145,165,172,178,188],"numerous":[15],"activities":[16],"processes":[18],"in":[19,40],"everyday":[20],"human":[21,38],"life.":[22],"Their":[23],"evolution":[24],"is":[25,159,196],"propelled":[26],"by":[27,161],"advancement":[29],"artificial":[31],"intelligence":[32,39],"(AI),":[33],"which":[34],"aims":[35],"emulate":[37],"execution":[42],"related":[44],"tasks.":[45],"The":[46,176],"remarkable":[47],"success":[48],"deep":[50],"learning":[51],"(DL)":[52],"computer":[54],"vision":[55],"(CV)":[56],"on":[57,192],"image":[58,168],"prompted":[60],"researchers":[61],"consider":[63],"its":[64],"application":[65],"time":[67,75,89,120,146,193],"series":[68,76,90,121,147,194],"multivariate":[70],"data.":[71],"this":[73],"context,":[74],"imaging":[77,122,148],"has":[78],"been":[79],"identified":[80],"as":[81],"research":[83],"field":[84,129,134],"for":[85,119,184],"transformation":[87,174],"(a":[92,98],"one-dimensional":[93],"format)":[95],"into":[96],"images":[97],"two-dimensional":[99],"format).":[101],"These":[102],"can":[104],"be":[105],"variables":[107],"or":[108,113],"features":[109],"a":[111,139],"system":[112],"phenomenon":[114],"under":[115],"consideration.":[116],"State-of-the-art":[117],"techniques":[118,183],"include":[123],"recurrence":[124],"plot":[125],"(RP),":[126],"Gramian":[127],"angular":[128],"(GAF),":[130],"Markov":[132],"transition":[133],"(MTF).":[135],"This":[136,156],"paper":[137],"proposes":[138],"novel,":[140],"robust,":[141],"simple":[143],"technique":[144,158],"using":[149],"Grayscale":[150],"Fingerprint":[151],"Features":[152],"Field":[153],"Imaging":[154],"(G3FI).":[155],"novel":[157,180],"distinguished":[160],"low":[163],"resolution":[164],"resulting":[167],"simplicity":[171],"procedure.":[175],"efficacy":[177],"state-of-the-art":[182],"enhancing":[185],"performance":[187],"CNN-based":[189],"classification":[190],"models":[191],"datasets":[195],"thoroughly":[197],"examined":[198],"compared.":[200]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-28T00:00:00"}
