{"id":"https://openalex.org/W3100409668","doi":"https://doi.org/10.1109/icassp39728.2021.9414512","title":"Discrete Cosine Transform Based Causal Convolutional Neural Network for Drift Compensation in Chemical Sensors","display_name":"Discrete Cosine Transform Based Causal Convolutional Neural Network for Drift Compensation in Chemical Sensors","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3100409668","doi":"https://doi.org/10.1109/icassp39728.2021.9414512","mag":"3100409668"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.06681","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058826860","display_name":"Diaa Badawi","orcid":"https://orcid.org/0000-0003-4979-5572"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Diaa Badawi","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL","University of Illinois at Chicago,Department of Electrical and Computer Engineering,Chicago,IL"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"University of Illinois at Chicago,Department of Electrical and Computer Engineering,Chicago,IL","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005077642","display_name":"Agamyrat Agambayev","orcid":"https://orcid.org/0000-0002-5078-7417"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Agamyrat Agambayev","raw_affiliation_strings":["School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ","Arizona State University School of Electrical, Computer and Energy Engineering Tempe AZ"],"affiliations":[{"raw_affiliation_string":"School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University School of Electrical, Computer and Energy Engineering Tempe AZ","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058946013","display_name":"Sule Ozev","orcid":"https://orcid.org/0000-0002-3636-715X"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sule Ozev","raw_affiliation_strings":["School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ","Arizona State University School of Electrical, Computer and Energy Engineering Tempe AZ"],"affiliations":[{"raw_affiliation_string":"School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University School of Electrical, Computer and Energy Engineering Tempe AZ","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080469744","display_name":"Ahmet Enis \u00c7etin","orcid":"https://orcid.org/0000-0002-3449-1958"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Enis Cetin","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL","University of Illinois at Chicago,Department of Electrical and Computer Engineering,Chicago,IL"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"University of Illinois at Chicago,Department of Electrical and Computer Engineering,Chicago,IL","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058826860"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00217707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8012","last_page":"8016"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11472","display_name":"Analytical Chemistry and Sensors","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1502","display_name":"Bioengineering"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11472","display_name":"Analytical Chemistry and Sensors","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1502","display_name":"Bioengineering"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.8357464075088501},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6915913224220276},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6631274223327637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6346395015716553},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6125186085700989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5913262367248535},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.503882110118866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3823840022087097},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06463757157325745}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.8357464075088501},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6915913224220276},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6631274223327637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6346395015716553},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6125186085700989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5913262367248535},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.503882110118866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3823840022087097},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06463757157325745},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":8,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2011.06681","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.06681","pdf_url":"https://arxiv.org/pdf/2011.06681","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:figshare.com:article/14721252","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/conference_contribution/Discrete_Cosine_Transform_Based_Causal_Convolutional_Neural_Network_for_Drift_Compensation_in_Chemical_Sensors/14721252","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"mag:3100409668","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2011.06681.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2011.06681","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2011.06681","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.17023/bv1q-hq28","is_oa":true,"landing_page_url":"https://doi.org/10.17023/bv1q-hq28","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.25417/uic.14721252","is_oa":true,"landing_page_url":"https://doi.org/10.25417/uic.14721252","pdf_url":null,"source":{"id":"https://openalex.org/S7407051395","display_name":"University of Illinois Chicago","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.25417/uic.14721252.v1","is_oa":true,"landing_page_url":"https://doi.org/10.25417/uic.14721252.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407051395","display_name":"University of Illinois Chicago","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.06681","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.06681","pdf_url":"https://arxiv.org/pdf/2011.06681","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1584393767","https://openalex.org/W1982094427","https://openalex.org/W2006395821","https://openalex.org/W2020033987","https://openalex.org/W2022851810","https://openalex.org/W2049368177","https://openalex.org/W2058763428","https://openalex.org/W2059285679","https://openalex.org/W2059477850","https://openalex.org/W2070664354","https://openalex.org/W2079296123","https://openalex.org/W2102080413","https://openalex.org/W2139598133","https://openalex.org/W2166465445","https://openalex.org/W2166858657","https://openalex.org/W2171017780","https://openalex.org/W2398969038","https://openalex.org/W2783662494","https://openalex.org/W2792764867","https://openalex.org/W2944367816","https://openalex.org/W2982172481","https://openalex.org/W3111877872","https://openalex.org/W6749825310","https://openalex.org/W6762295098"],"related_works":["https://openalex.org/W3160069202","https://openalex.org/W2984832126","https://openalex.org/W2932416803","https://openalex.org/W2363397295","https://openalex.org/W1501129248","https://openalex.org/W2115025371","https://openalex.org/W2106811279","https://openalex.org/W3123078698","https://openalex.org/W3186526634","https://openalex.org/W1992946554","https://openalex.org/W2894982584","https://openalex.org/W2900255851","https://openalex.org/W3136671356","https://openalex.org/W2797758148","https://openalex.org/W2947260180","https://openalex.org/W2106110033","https://openalex.org/W3031729501","https://openalex.org/W3162983744","https://openalex.org/W1802336642","https://openalex.org/W2940450111"],"abstract_inverted_index":{"Sensor":[0],"drift":[1,41,66,90,118],"is":[2,126],"a":[3,25,32,61,86],"major":[4],"problem":[5],"in":[6,51],"chemical":[7,18,104],"sensors":[8],"that":[9,78,110],"requires":[10],"addressing":[11],"for":[12],"reliable":[13],"and":[14,59,99,116],"accurate":[15,115],"detection":[16],"of":[17,64],"analytes.":[19],"In":[20,43],"this":[21],"paper,":[22],"we":[23,47,111],"develop":[24],"causal":[26],"convolutional":[27],"neural":[28],"network":[29],"(CNN)":[30],"with":[31],"Discrete":[33],"Cosine":[34],"Transform":[35],"(DCT)":[36],"layer":[37],"to":[38,55,84],"estimate":[39,119],"the":[40,44,52,57,65,94,122],"signal.":[42,67,91],"DCT":[45,79],"module,":[46],"apply":[48],"soft-thresholding":[49],"nonlinearity":[50],"transform":[53],"domain":[54],"denoise":[56],"data":[58,98],"obtain":[60],"sparse":[62],"representation":[63],"The":[68],"soft-threshold":[69],"values":[70],"are":[71,82],"learned":[72],"during":[73],"training.":[74],"Our":[75,107],"results":[76,108],"show":[77,109],"layer-based":[80],"CNNs":[81],"able":[83],"produce":[85],"slowly":[87],"varying":[88],"baseline":[89],"We":[92],"train":[93],"CNN":[95],"on":[96,102],"synthetic":[97],"test":[100],"it":[101],"real":[103],"sensor":[105,124],"data.":[106],"can":[112],"have":[113],"an":[114],"smooth":[117],"even":[120],"when":[121],"observed":[123],"signal":[125],"very":[127],"noisy.":[128]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
