{"id":"https://openalex.org/W4415524537","doi":"https://doi.org/10.1109/mlsp62443.2025.11204305","title":"APA: Domain Generalization Using Frequency Based Augmentation","display_name":"APA: Domain Generalization Using Frequency Based Augmentation","publication_year":2025,"publication_date":"2025-08-31","ids":{"openalex":"https://openalex.org/W4415524537","doi":"https://doi.org/10.1109/mlsp62443.2025.11204305"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp62443.2025.11204305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp62443.2025.11204305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5119400220","display_name":"Sina Salehnia","orcid":null},"institutions":[{"id":"https://openalex.org/I134235054","display_name":"Sabanc\u0131 \u00dcniversitesi","ror":"https://ror.org/049asqa32","country_code":"TR","type":"education","lineage":["https://openalex.org/I134235054"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Sina Salehnia","raw_affiliation_strings":["Sabancı University,Faculty of Engineering and Natural Sciences,Istanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sabancı University,Faculty of Engineering and Natural Sciences,Istanbul,Türkiye","institution_ids":["https://openalex.org/I134235054"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051657734","display_name":"\u00d6znur Ta\u015ftan","orcid":"https://orcid.org/0000-0001-7058-5372"},"institutions":[{"id":"https://openalex.org/I134235054","display_name":"Sabanc\u0131 \u00dcniversitesi","ror":"https://ror.org/049asqa32","country_code":"TR","type":"education","lineage":["https://openalex.org/I134235054"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Oznur Tastan","raw_affiliation_strings":["Sabancı University,Faculty of Engineering and Natural Sciences,Istanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sabancı University,Faculty of Engineering and Natural Sciences,Istanbul,Türkiye","institution_ids":["https://openalex.org/I134235054"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026370111","display_name":"Erchan Aptoula","orcid":"https://orcid.org/0000-0001-6168-2883"},"institutions":[{"id":"https://openalex.org/I134235054","display_name":"Sabanc\u0131 \u00dcniversitesi","ror":"https://ror.org/049asqa32","country_code":"TR","type":"education","lineage":["https://openalex.org/I134235054"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Erchan Aptoula","raw_affiliation_strings":["Sabancı University,Faculty of Engineering and Natural Sciences,Istanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sabancı University,Faculty of Engineering and Natural Sciences,Istanbul,Türkiye","institution_ids":["https://openalex.org/I134235054"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I134235054"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14164025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.714900016784668,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.714900016784668,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.6777999997138977,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7070000171661377},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6407999992370605},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.593999981880188},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5426999926567078},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5354999899864197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5313000082969666},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49970000982284546},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.35690000653266907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.713699996471405},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7070000171661377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6510999798774719},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6407999992370605},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.593999981880188},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5426999926567078},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5354999899864197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5313000082969666},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49970000982284546},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48590001463890076},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C2985998994","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Source model","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30140000581741333},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2962000072002411},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.2632000148296356}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mlsp62443.2025.11204305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp62443.2025.11204305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:research.sabanciuniv.edu:52628","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402254","display_name":"Sabanci University","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I134235054","host_organization_name":"Sabanc\u0131 \u00dcniversitesi","host_organization_lineage":["https://openalex.org/I134235054"],"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2017814585","https://openalex.org/W2031489346","https://openalex.org/W2110764733","https://openalex.org/W2194775991","https://openalex.org/W2763549966","https://openalex.org/W2903867357","https://openalex.org/W2963043696","https://openalex.org/W2964288524","https://openalex.org/W3023104975","https://openalex.org/W3035294798","https://openalex.org/W3109957618","https://openalex.org/W3175215201","https://openalex.org/W4289639938","https://openalex.org/W4322753738","https://openalex.org/W4385245566","https://openalex.org/W4386083080","https://openalex.org/W4387643481","https://openalex.org/W4389990420","https://openalex.org/W4392909953","https://openalex.org/W4402754058"],"related_works":[],"abstract_inverted_index":{"Domain":[0],"shift":[1],"remains":[2],"a":[3,57,84],"major":[4],"challenge":[5],"in":[6],"computer":[7],"vision,":[8],"where":[9],"models":[10,82,125],"trained":[11,113,126],"on":[12,17,97,127],"source":[13,39],"domain(s)":[14],"perform":[15],"poorly":[16],"unseen":[18],"target":[19,47],"domains.":[20],"One":[21],"way":[22],"to":[23,41,83,123],"address":[24],"this":[25,50],"issue":[26],"is":[27,112],"by":[28,65],"using":[29],"data":[30],"augmentation":[31,59],"techniques,":[32],"which":[33,111],"generate":[34],"synthetic":[35],"images":[36,40,64],"of":[37,45,70,87],"the":[38,46,67,108,128],"mimic":[42],"potential":[43],"characteristics":[44],"domain.":[48],"In":[49],"work,":[51],"we":[52],"introduce":[53],"Amplitude-Phase":[54],"Augmentation":[55],"(APA),":[56],"frequency-domain":[58],"technique.":[60],"APA":[61,106],"generates":[62],"cross-domain":[63],"multiplying":[66],"amplitude":[68],"spectra":[69],"image":[71],"pairs":[72],"while":[73],"preserving":[74],"their":[75],"original":[76,115],"phase":[77],"information.":[78],"This":[79],"approach":[80],"exposes":[81],"broader":[85],"spectrum":[86],"frequency-based":[88],"variations,":[89],"simulating":[90],"diverse":[91],"domain":[92],"styles.":[93],"We":[94],"demonstrate":[95],"that":[96],"two":[98,103],"different":[99,104],"datasets":[100],"and":[101,117,131],"with":[102,114],"backbones,":[105],"outperforms":[107],"baseline":[109],"model,":[110],"images,":[116],"also":[118],"achieves":[119],"competitive":[120],"results":[121],"compared":[122],"other":[124],"same":[129],"backbones":[130],"datasets.":[132],"Code":[133],"available":[134],"at":[135],"https://github.com/sina-nuel/APA.":[136]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-24T00:00:00"}