{"id":"https://openalex.org/W4390284987","doi":"https://doi.org/10.1109/tpami.2023.3347617","title":"Reconstructing Randomly Masked Spectra Helps DNNs Identify Discriminant Wavenumbers","display_name":"Reconstructing Randomly Masked Spectra Helps DNNs Identify Discriminant Wavenumbers","publication_year":2023,"publication_date":"2023-12-27","ids":{"openalex":"https://openalex.org/W4390284987","doi":"https://doi.org/10.1109/tpami.2023.3347617","pmid":"https://pubmed.ncbi.nlm.nih.gov/38150338"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3347617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3347617","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5103105774","display_name":"Yingying Wu","orcid":"https://orcid.org/0000-0002-8605-5621"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingying Wu","raw_affiliation_strings":["Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8605-5621","affiliations":[{"raw_affiliation_string":"Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101599789","display_name":"Jinchao Liu","orcid":"https://orcid.org/0000-0003-2559-7512"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinchao Liu","raw_affiliation_strings":["Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2559-7512","affiliations":[{"raw_affiliation_string":"Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322975","display_name":"Yan Wang","orcid":"https://orcid.org/0000-0003-4346-692X"},"institutions":[{"id":"https://openalex.org/I4210108355","display_name":"VisionTree","ror":"https://ror.org/01sfnbz84","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210108355"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["VisionMetric Ltd., Canterbury, U.K"],"raw_orcid":"https://orcid.org/0000-0003-4346-692X","affiliations":[{"raw_affiliation_string":"VisionMetric Ltd., Canterbury, U.K","institution_ids":["https://openalex.org/I4210108355"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024619073","display_name":"Stuart Gibson","orcid":"https://orcid.org/0000-0002-7981-241X"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stuart Gibson","raw_affiliation_strings":["School of Physics and Astronomy, University of Kent, Canterbury, U.K"],"raw_orcid":"https://orcid.org/0000-0002-7981-241X","affiliations":[{"raw_affiliation_string":"School of Physics and Astronomy, University of Kent, Canterbury, U.K","institution_ids":["https://openalex.org/I20581793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068276075","display_name":"Margarita Osadchy","orcid":"https://orcid.org/0000-0001-5480-5099"},"institutions":[{"id":"https://openalex.org/I91203450","display_name":"University of Haifa","ror":"https://ror.org/02f009v59","country_code":"IL","type":"education","lineage":["https://openalex.org/I91203450"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Margarita Osadchy","raw_affiliation_strings":["Department of Computer Science, Haifa University, Haifa, Israel"],"raw_orcid":"https://orcid.org/0000-0001-5480-5099","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Haifa University, Haifa, Israel","institution_ids":["https://openalex.org/I91203450"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058644546","display_name":"Yongchun Fang","orcid":"https://orcid.org/0000-0002-3061-2708"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongchun Fang","raw_affiliation_strings":["Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-3061-2708","affiliations":[{"raw_affiliation_string":"Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5103105774"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":1.1585,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74331728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"46","issue":"5","first_page":"3845","last_page":"3861"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.740947961807251},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7065613269805908},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6832356452941895},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.6449196338653564},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5290666222572327},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5289934873580933},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4667869806289673},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4610629975795746},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.43419912457466125},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4254390001296997},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.10307750105857849}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.740947961807251},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7065613269805908},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6832356452941895},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.6449196338653564},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5290666222572327},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5289934873580933},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4667869806289673},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4610629975795746},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.43419912457466125},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4254390001296997},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.10307750105857849},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2023.3347617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3347617","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:38150338","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38150338","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:kar.kent.ac.uk:104884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/TPAMI.2023.3347617>)","pdf_url":null,"source":{"id":"https://openalex.org/S4377196264","display_name":"Kent Academic Repository (University of Kent)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20581793","host_organization_name":"University of Kent","host_organization_lineage":["https://openalex.org/I20581793"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G7645675549","display_name":null,"funder_award_id":"62076140","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8527692473","display_name":null,"funder_award_id":"EP/S018964/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W153185079","https://openalex.org/W1901129140","https://openalex.org/W1986902094","https://openalex.org/W2001735456","https://openalex.org/W2016365402","https://openalex.org/W2029089404","https://openalex.org/W2494566811","https://openalex.org/W2523062496","https://openalex.org/W2606412288","https://openalex.org/W2618530766","https://openalex.org/W2746314669","https://openalex.org/W2752532133","https://openalex.org/W2762818368","https://openalex.org/W2770173563","https://openalex.org/W2783482415","https://openalex.org/W2798365772","https://openalex.org/W2798680770","https://openalex.org/W2803714405","https://openalex.org/W2807326971","https://openalex.org/W2883273084","https://openalex.org/W2884436604","https://openalex.org/W2886192117","https://openalex.org/W2891747104","https://openalex.org/W2896457183","https://openalex.org/W2898664946","https://openalex.org/W2903091095","https://openalex.org/W2911514609","https://openalex.org/W2914001277","https://openalex.org/W2914865775","https://openalex.org/W2921310231","https://openalex.org/W2962793481","https://openalex.org/W2962858109","https://openalex.org/W2963420272","https://openalex.org/W2963622428","https://openalex.org/W2963845150","https://openalex.org/W2970353953","https://openalex.org/W2982482221","https://openalex.org/W2990349864","https://openalex.org/W2992308087","https://openalex.org/W2992838650","https://openalex.org/W2998508940","https://openalex.org/W3035524670","https://openalex.org/W3037874813","https://openalex.org/W3094483422","https://openalex.org/W3094502228","https://openalex.org/W3100410998","https://openalex.org/W3105938520","https://openalex.org/W3126121388","https://openalex.org/W3134567495","https://openalex.org/W3135793694","https://openalex.org/W3160063135","https://openalex.org/W3169228979","https://openalex.org/W3197865018","https://openalex.org/W3204255034","https://openalex.org/W4225809603","https://openalex.org/W4226422926","https://openalex.org/W4294643831","https://openalex.org/W4313156423","https://openalex.org/W6717697761","https://openalex.org/W6736057607","https://openalex.org/W6743428213","https://openalex.org/W6745213946","https://openalex.org/W6745560452","https://openalex.org/W6746638498","https://openalex.org/W6747939174","https://openalex.org/W6752940074","https://openalex.org/W6754654810","https://openalex.org/W6780041708","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"Nondestructive":[0],"detection":[1],"methods,":[2],"based":[3],"on":[4,126],"vibrational":[5,30,46],"spectroscopy,":[6],"are":[7,90,107,119],"vitally":[8],"important":[9],"in":[10],"a":[11,66,77,188],"wide":[12],"range":[13],"of":[14,74,135,157],"applications":[15],"including":[16],"industrial":[17],"chemistry,":[18],"pharmacy":[19],"and":[20,58,85,116,129,152,159,161,179,193],"national":[21],"defense.":[22],"Recently,":[23],"deep":[24],"learning":[25],"has":[26],"been":[27],"introduced":[28],"into":[29],"spectroscopy":[31],"showing":[32],"great":[33],"potential.":[34],"Different":[35],"from":[36,101],"images,":[37],"text,":[38],"etc.":[39],"that":[40,80,89,163],"offer":[41],"large":[42],"labeled":[43],"data":[44,48],"sets,":[45],"spectroscopic":[47],"is":[49,76,177],"very":[50],"limited,":[51],"which":[52],"requires":[53],"novel":[54],"concepts":[55],"beyond":[56],"transfer":[57],"meta":[59],"learning.":[60,196],"To":[61],"tackle":[62],"this,":[63],"we":[64],"propose":[65],"task-enhanced":[67],"augmentation":[68],"network":[69],"(TeaNet).":[70],"The":[71,114],"key":[72],"component":[73],"TeaNet":[75,145,158],"reconstruction":[78,115],"module":[79],"inputs":[81],"randomly":[82],"masked":[83],"spectra":[84],"outputs":[86],"reconstructed":[87],"samples":[88,106],"similar":[91],"to":[92,109,166,173,184,190],"the":[93,102,111,133,136,140,154],"original":[94],"ones,":[95],"but":[96],"include":[97],"additional":[98],"variations":[99],"learned":[100],"domain.":[103],"These":[104],"augmented":[105],"used":[108],"train":[110],"classification":[112],"model.":[113],"prediction":[117],"parts":[118],"trained":[120],"simultaneously,":[121],"end-to-end":[122],"with":[123],"back-propagation.":[124],"Results":[125],"both":[127],"synthetic":[128,143],"real-world":[130],"datasets":[131],"verified":[132],"superiority":[134],"proposed":[137],"method.":[138],"In":[139],"most":[141],"difficult":[142],"scenarios":[144],"outperformed":[146],"CNN":[147],"by":[148],"17%.":[149],"We":[150],"visualized":[151],"analysed":[153],"neuron":[155],"responses":[156],"CNN,":[160],"found":[162],"TeaNet's":[164],"ability":[165],"identify":[167],"discriminant":[168],"wavenumbers":[169],"was":[170],"excellent":[171],"compared":[172],"CNN.":[174],"Our":[175],"approach":[176],"general":[178],"can":[180],"be":[181],"easily":[182],"adapted":[183],"other":[185],"domains,":[186],"offering":[187],"solution":[189],"more":[191],"accurate":[192],"interpretable":[194],"few-shot":[195]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}