{"id":"https://openalex.org/W4392910560","doi":"https://doi.org/10.1109/icassp48485.2024.10447415","title":"Prototype-Guided Masking for Unsupervised Domain Adaptation","display_name":"Prototype-Guided Masking for Unsupervised Domain Adaptation","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392910560","doi":"https://doi.org/10.1109/icassp48485.2024.10447415"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447415","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101675126","display_name":"Kaiwen Chen","orcid":"https://orcid.org/0000-0001-6816-6910"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kai-Wen Chen","raw_affiliation_strings":["National Chung Cheng University,Computer Science and Information Engineering,Taiwan","Computer Science and Information Engineering, National Chung Cheng University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Computer Science and Information Engineering,Taiwan","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Computer Science and Information Engineering, National Chung Cheng University, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067534025","display_name":"Chen-Kuo Chiang","orcid":"https://orcid.org/0000-0001-5276-1109"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chen-Kuo Chiang","raw_affiliation_strings":["National Chung Cheng University,Computer Science and Information Engineering,Taiwan","Computer Science and Information Engineering, National Chung Cheng University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Computer Science and Information Engineering,Taiwan","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Computer Science and Information Engineering, National Chung Cheng University, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148099254"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6055","last_page":"6059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.792900025844574,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.792900025844574,"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/computer-science","display_name":"Computer science","score":0.7594383955001831},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.72096186876297},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6503145694732666},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.554336428642273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3811608552932739},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3446250259876251},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08695703744888306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7594383955001831},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.72096186876297},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6503145694732666},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.554336428642273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3811608552932739},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3446250259876251},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08695703744888306},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447415","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2340897893","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2795155917","https://openalex.org/W2963073217","https://openalex.org/W2972285644","https://openalex.org/W3025869703","https://openalex.org/W3120804725","https://openalex.org/W3134134173","https://openalex.org/W3170700905","https://openalex.org/W3175294391","https://openalex.org/W3175308890","https://openalex.org/W3195892675","https://openalex.org/W3217147624","https://openalex.org/W4295788754","https://openalex.org/W4308503280","https://openalex.org/W4312768455","https://openalex.org/W4386047746","https://openalex.org/W6750109254"],"related_works":["https://openalex.org/W3081694532","https://openalex.org/W2997567050","https://openalex.org/W1969211203","https://openalex.org/W1517958729","https://openalex.org/W2092272653","https://openalex.org/W1483272040","https://openalex.org/W4283377908","https://openalex.org/W1992704972","https://openalex.org/W1533421371","https://openalex.org/W4394775207"],"abstract_inverted_index":{"In":[0],"the":[1,8,16,23,28,33,49,91,99,146,158,177],"domain":[2,18,25],"of":[3,30,75,93,149,154,160],"Unsupervised":[4],"Domain":[5],"Adaptation":[6],"(UDA),":[7],"training":[9],"process":[10],"leverages":[11],"both":[12],"labeled":[13],"data":[14,21],"from":[15,22,129],"source":[17],"and":[19,169],"unlabeled":[20],"target":[24,34],"to":[26,32,41,54,63,88,125,135,139,167,187],"facilitate":[27],"transfer":[29],"knowledge":[31],"domain.":[35],"Previous":[36],"UDA":[37],"methods":[38],"have":[39],"sought":[40],"improve":[42],"robust":[43],"visual":[44],"recognition":[45,79],"by":[46],"capitalizing":[47],"on":[48,127,190],"consistency":[50],"among":[51],"masked":[52],"images":[53],"learn":[55],"spatial":[56],"context":[57],"relations.":[58],"However,":[59],"it":[60],"is":[61,157,165],"imperative":[62],"acknowledge":[64],"that":[65,141,176],"different":[66],"regions":[67],"within":[68],"an":[69],"image":[70],"may":[71],"hold":[72],"varying":[73],"degrees":[74],"significance":[76],"across":[77,192],"various":[78],"tasks.":[80],"The":[81],"conventional":[82],"approach":[83,156],"typically":[84],"involves":[85],"random":[86],"masking":[87],"images,":[89],"neglecting":[90],"evaluation":[92],"sample":[94],"difficulty":[95],"or":[96],"ease":[97],"during":[98],"model":[100],"learning":[101,128],"process.":[102],"To":[103],"tackle":[104],"this":[105,119,155],"challenge,":[106],"we":[107],"introduce":[108],"a":[109],"novel":[110],"technique,":[111],"called":[112],"Prototype-Guided":[113,179],"Masking,":[114],"for":[115],"semantic":[116,194],"segmentation":[117,195],"in":[118,145],"paper.":[120],"It":[121],"enforces":[122],"deep":[123],"models":[124],"concentrate":[126],"more":[130],"challenging":[131],"regions,":[132],"as":[133],"opposed":[134],"dedicating":[136],"excessive":[137],"attention":[138],"samples":[140],"are":[142],"easily":[143],"distinguishable":[144],"initial":[147],"stages":[148],"training.":[150],"A":[151],"key":[152],"component":[153],"introduction":[159],"prototype":[161],"confidence":[162],"score,":[163],"which":[164],"utilized":[166],"assess":[168],"selectively":[170],"mask":[171],"images.":[172],"Experimental":[173],"results":[174],"demonstrate":[175],"proposed":[178],"Masking":[180],"yields":[181],"highly":[182],"competitive":[183],"outcomes":[184],"when":[185],"compared":[186],"state-of-the-art":[188],"performance":[189],"benchmarks":[191],"multiple":[193],"datasets.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}