{"id":"https://openalex.org/W7138006806","doi":"https://doi.org/10.1609/aaai.v40i16.38412","title":"SinBasis Networks: Matrix-Equivalent Feature Extraction for Wave-Like Optical Spectrograms","display_name":"SinBasis Networks: Matrix-Equivalent Feature Extraction for Wave-Like Optical Spectrograms","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138006806","doi":"https://doi.org/10.1609/aaai.v40i16.38412"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i16.38412","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i16.38412","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38412/42374","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38412/42374","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129727799","display_name":"Yuzhou Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuzhou Zhu","raw_affiliation_strings":["Dalian University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129733212","display_name":"Zheng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zhang","raw_affiliation_strings":["Dalian University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129658410","display_name":"Ruyi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruyi Zhang","raw_affiliation_strings":["Zhejiang Gongshang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University","institution_ids":["https://openalex.org/I75059550"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129731686","display_name":"Liang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Zhou","raw_affiliation_strings":["Dalian University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129727799"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20889101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"16","first_page":"14014","last_page":"14021"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.1347000002861023,"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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.1347000002861023,"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/T11996","display_name":"Random lasers and scattering media","score":0.10939999669790268,"subfield":{"id":"https://openalex.org/subfields/3102","display_name":"Acoustics and Ultrasonics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11897","display_name":"Digital Holography and Microscopy","score":0.07400000095367432,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/streaking","display_name":"Streaking","score":0.6718999743461609},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.6316999793052673},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5476999878883362},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5375999808311462},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5339999794960022},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48100000619888306},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.41269999742507935},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4108000099658966},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.40139999985694885}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6776000261306763},{"id":"https://openalex.org/C33600429","wikidata":"https://www.wikidata.org/wiki/Q2384832","display_name":"Streaking","level":2,"score":0.6718999743461609},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.6316999793052673},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5476999878883362},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5375999808311462},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5339999794960022},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4650999903678894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45249998569488525},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4108000099658966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4066999852657318},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C189645446","wikidata":"https://www.wikidata.org/wiki/Q350865","display_name":"Mirroring","level":2,"score":0.39820000529289246},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.3792000114917755},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.35760000348091125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3425000011920929},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.3149000108242035},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i16.38412","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i16.38412","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38412/42374","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i16.38412","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i16.38412","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38412/42374","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.4153549373149872}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138006806.pdf","grobid_xml":"https://content.openalex.org/works/W7138006806.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Wave-like":[0],"images\u2014from":[1],"attosecond":[2,97],"streaking":[3,98],"spectrograms":[4],"to":[5,58,77,83,154],"optical":[6],"spectra,":[7,106],"audio":[8],"mel-spectrograms":[9,107],"and":[10,31,68,80,104,110,122,131],"periodic":[11,78],"video":[12],"frames\u2014encode":[13],"critical":[14],"harmonic":[15],"structures":[16],"that":[17,28],"elude":[18],"conventional":[19],"feature":[20,47],"extractors.":[21],"We":[22],"propose":[23],"a":[24,88,150],"unified,":[25],"matrix-equivalent":[26],"framework":[27],"reinterprets":[29],"convolution":[30],"attention":[32],"as":[33,42],"linear":[34],"transforms":[35,64],"on":[36,87],"flattened":[37],"inputs,":[38],"revealing":[39],"filter":[40],"weights":[41],"basis":[43],"vectors":[44],"spanning":[45],"latent":[46],"subspaces.":[48],"To":[49],"infuse":[50],"spectral":[51],"priors":[52],"we":[53],"apply":[54],"elementwise":[55],"sin(\u00b7)":[56],"mappings":[57],"each":[59],"weight":[60],"matrix.":[61],"Embedding":[62],"these":[63],"into":[65],"CNN,":[66],"ViT":[67],"Capsule":[69],"architectures":[70],"yields":[71],"Sin-Basis":[72,146],"Networks":[73,147],"with":[74],"heightened":[75],"sensitivity":[76],"motifs":[79],"built-in":[81],"invariance":[82],"spatial":[84],"shifts.":[85],"Experiments":[86],"diverse":[89],"collection":[90],"of":[91,101],"wave-like":[92],"image":[93],"datasets\u2014including":[94],"80,000":[95],"synthetic":[96],"spectrograms,":[99],"thousands":[100],"Raman,":[102],"photoluminescence":[103],"FTIR":[105],"from":[108,113],"AudioSet":[109],"cycle-pattern":[111],"frames":[112],"Kinetics\u2014demonstrate":[114],"substantial":[115],"gains":[116],"in":[117,143],"reconstruction":[118],"accuracy,":[119],"translational":[120],"robustness":[121],"zero-shot":[123],"cross-domain":[124],"transfer.":[125],"Theoretical":[126],"analysis":[127],"via":[128],"matrix":[129],"isomorphism":[130],"Mercer-kernel":[132],"truncation":[133],"quantifies":[134],"how":[135],"sinusoidal":[136],"reparametrization":[137],"enriches":[138],"expressivity":[139],"while":[140],"preserving":[141],"stability":[142],"data-scarce":[144],"regimes.":[145],"thus":[148],"offer":[149],"lightweight,":[151],"physics-informed":[152],"approach":[153],"deep":[155],"learning":[156],"across":[157],"all":[158],"wave-form":[159],"imaging":[160],"modalities.":[161]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-03-18T00:00:00"}
