{"id":"https://openalex.org/W3135826267","doi":null,"title":"VISUAL AND SEMANTIC KNOWLEDGE TRANSFER FOR NOVEL TASKS","display_name":"VISUAL AND SEMANTIC KNOWLEDGE TRANSFER FOR NOVEL TASKS","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W3135826267","mag":"3135826267"},"language":"en","primary_location":{"id":"pmh:oai:scholarshare.temple.edu:20.500.12613/3885","doi":null,"is_oa":false,"landing_page_url":"https://scholarshare.temple.edu/bitstream/20.500.12613/3885/1/Ye_temple_0225E_13822.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306402624","display_name":"TUScholarShare (Temple University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I84392919","host_organization_name":"Temple University","host_organization_lineage":["https://openalex.org/I84392919"],"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":"Thesis/Dissertation"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Meng Ye","orcid":"https://orcid.org/0000-0001-9175-9773","observed_orcids":["https://orcid.org/0000-0001-9175-9773"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Meng Ye","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9175-9773","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":1.0,"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":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/zero-shot-learning","display_name":"zero-shot learning","score":0.9190000295639038},{"id":"https://openalex.org/keywords/domain-shift","display_name":"domain shift","score":0.9240000247955322},{"id":"https://openalex.org/keywords/progressive-training","display_name":"progressive training","score":0.9760000109672546},{"id":"https://openalex.org/keywords/scene-classification","display_name":"scene classification","score":0.718999981880188},{"id":"https://openalex.org/keywords/object-detectors","display_name":"object detectors","score":0.5669999718666077},{"id":"https://openalex.org/keywords/word-embeddings","display_name":"word embeddings","score":0.9440000057220459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5625550746917725},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4293912947177887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3817618787288666}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:scholarshare.temple.edu:20.500.12613/3885","doi":null,"is_oa":false,"landing_page_url":"https://scholarshare.temple.edu/bitstream/20.500.12613/3885/1/Ye_temple_0225E_13822.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306402624","display_name":"TUScholarShare (Temple University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I84392919","host_organization_name":"Temple University","host_organization_lineage":["https://openalex.org/I84392919"],"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":"Thesis/Dissertation"},{"id":"mag:3135826267","doi":null,"is_oa":false,"landing_page_url":"https://scholarshare.temple.edu/handle/20.500.12613/3885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W93016980","https://openalex.org/W331145617","https://openalex.org/W652269744","https://openalex.org/W1500937733","https://openalex.org/W1590510366","https://openalex.org/W1614298861","https://openalex.org/W1686810756","https://openalex.org/W2032699694","https://openalex.org/W2040999325","https://openalex.org/W2048679005","https://openalex.org/W2070148066","https://openalex.org/W2098411764","https://openalex.org/W2102605133","https://openalex.org/W2109933951","https://openalex.org/W2117539524","https://openalex.org/W2118718620","https://openalex.org/W2120779048","https://openalex.org/W2123024445","https://openalex.org/W2123099218","https://openalex.org/W2125666396","https://openalex.org/W2128053425","https://openalex.org/W2132175002","https://openalex.org/W2133556223","https://openalex.org/W2134270519","https://openalex.org/W2134670479","https://openalex.org/W2149466042","https://openalex.org/W2151103935","https://openalex.org/W2153579005","https://openalex.org/W2155541015","https://openalex.org/W2159328468","https://openalex.org/W2161969291","https://openalex.org/W2166473218","https://openalex.org/W2168356304","https://openalex.org/W2191616647","https://openalex.org/W2194775991","https://openalex.org/W2250539671","https://openalex.org/W2296073425","https://openalex.org/W2334493732","https://openalex.org/W2400717490","https://openalex.org/W2504108613","https://openalex.org/W2514265125","https://openalex.org/W2541843346","https://openalex.org/W2740306440","https://openalex.org/W2799215068","https://openalex.org/W2962714319","https://openalex.org/W2962830213","https://openalex.org/W2962879692","https://openalex.org/W2963351448","https://openalex.org/W2963542991","https://openalex.org/W2963846885","https://openalex.org/W2963960318","https://openalex.org/W2978762605","https://openalex.org/W3106051827","https://openalex.org/W6941183308"],"related_works":["https://openalex.org/W2900819232","https://openalex.org/W6926835166","https://openalex.org/W2905966801","https://openalex.org/W3014611493","https://openalex.org/W3115489368","https://openalex.org/W3137518533","https://openalex.org/W3109904325","https://openalex.org/W3036608216","https://openalex.org/W3192668928","https://openalex.org/W4362510266"],"abstract_inverted_index":{"Data":[0],"is":[1,57,64,117,125,130,142,162,198,230,290],"a":[2,6,23,62,67,147,176,228,288,305,325,329,354,374],"critical":[3],"component":[4],"in":[5,52,121,137,267,284,343,367],"supervised":[7,54,258],"machine":[8],"learning":[9,15,55,197],"system.":[10],"Many":[11],"successful":[12],"applications":[13,286],"of":[14,26,44,46,134,151,175,195,224,234,333,398],"systems":[16,56],"on":[17,22,39,66,76,95,178,244,439],"various":[18,285],"tasks":[19,136],"are":[20],"based":[21],"large":[24],"amount":[25,133],"labeled":[27,47],"data.":[28],"For":[29,226],"example,":[30,227],"deep":[31],"convolutional":[32],"neural":[33],"networks":[34],"have":[35,186,212,220],"surpassed":[36],"human":[37],"performance":[38,174],"ImageNet":[40],"classification,":[41],"which":[42,161,250,336,358,382],"consists":[43],"millions":[45],"images.":[48],"However,":[49,111],"one":[50,98],"challenge":[51],"conventional":[53,257],"their":[58],"generalization":[59],"ability.":[60],"Once":[61],"model":[63,93,177,229,306,326],"trained":[65,401],"specific":[68,193],"dataset,":[69],"it":[70,124,251],"can":[71,303,426],"only":[72],"perform":[73,272],"the":[74,92,109,138,156,168,173,179,204,213,221,268,278,339,364,408,423],"task":[75,316],"those":[77],"\\emph{seen}":[78],"classes":[79],"and":[80,102,106,114,119,182,209,236,240,247,310,378,430,435],"cannot":[81],"be":[82,242,281],"used":[83],"for":[84,149,158,238,410,414],"novel":[85],"\\emph{unseen}":[86],"classes.":[87,225],"In":[88,296],"order":[89],"to":[90,100,145,171,271,280,292,317,363],"make":[91],"work":[94],"new":[96,104],"classes,":[97],"has":[99,252],"collect":[101],"label":[103],"data":[105,113,166,188,215,266],"then":[107],"re-train":[108],"model.":[110],"collecting":[112],"labeling":[115],"them":[116],"labor-intensive":[118],"costly,":[120],"some":[122],"cases,":[123],"even":[126],"impossible.":[127],"Also,":[128],"there":[129],"an":[131,349,368],"enormous":[132],"different":[135,187,190],"real":[139],"world.":[140],"It":[141,201],"not":[143,219,263],"applicable":[144],"create":[146],"dataset":[148],"each":[150,415],"them.":[152],"These":[153],"problems":[154],"raise":[155],"need":[157,409],"Transfer":[159],"Learning,":[160],"aimed":[163],"at":[164],"using":[165],"from":[167,256,314,385,402],"\\emph{source}":[169,207,315,360],"domain":[170,208,211,270,340,361,366],"improve":[172],"\\emph{target}":[180,210,269,318,365],"domain,":[181],"these":[183],"two":[184],"domains":[185],"or":[189],"tasks.":[191,392],"One":[192],"case":[194],"transfer":[196,308,428],"Zero-Shot":[199,260,344],"Learning.":[200,345],"deals":[202],"with":[203,353],"situation":[205],"where":[206,287],"same":[214,222],"distribution":[216],"but":[217],"do":[218],"set":[223],"given":[231],"animal":[232],"images":[233],"`cat'":[235],"`dog'":[237],"training":[239,265,356],"will":[241],"tested":[243],"classifying":[245],"'tiger'":[246],"'wolf'":[248],"images,":[249],"never":[253],"seen.":[254],"Different":[255],"learning,":[259],"Learning":[261],"does":[262],"require":[264],"classification.":[273],"This":[274],"property":[275],"gives":[276],"ZSL":[277,377],"potential":[279],"broadly":[282],"applied":[283],"system":[289],"expected":[291],"tackle":[293],"unexpected":[294],"situations.":[295],"this":[297],"dissertation,":[298],"we":[299,323,347,372,420],"develop":[300,324,348],"algorithms":[301],"that":[302,327,422],"help":[304,337],"effectively":[307,427],"visual":[309,331,429],"semantic":[311,334,412,431],"knowledge":[312,362,384,432],"learned":[313],"task.":[319],"More":[320],"specifically,":[321],"first":[322],"learns":[328],"uniform":[330],"representation":[332],"attributes,":[335],"alleviate":[338],"shift":[341],"problem":[342],"Second,":[346],"ensemble":[350],"network":[351],"architecture":[352],"progressive":[355],"scheme,":[357],"transfers":[359,383],"end-to-end":[369],"manner.":[370],"Lastly,":[371],"move":[373],"step":[375],"beyond":[376],"explore":[379],"Label-less":[380],"Classification,":[381],"pre-trained":[386],"object":[387],"detectors":[388],"into":[389],"scene":[390],"classification":[391,395],"Our":[393],"label-less":[394],"takes":[396],"advantage":[397],"word":[399],"embeddings":[400],"unorganized":[403],"online":[404],"text,":[405],"thus":[406],"eliminating":[407],"expert-defined":[411],"attributes":[413],"class.":[416],"Through":[417],"comprehensive":[418],"experiments,":[419],"show":[421],"proposed":[424],"methods":[425],"between":[433],"tasks,":[434],"achieve":[436],"state-of-the-art":[437],"performances":[438],"standard":[440],"datasets.":[441]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2021-03-15T00:00:00"}