{"id":"https://openalex.org/W2063806042","doi":"https://doi.org/10.1109/icapr.2015.7050701","title":"Domain adaptation using weighted sub-space sampling for object categorization","display_name":"Domain adaptation using weighted sub-space sampling for object categorization","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2063806042","doi":"https://doi.org/10.1109/icapr.2015.7050701","mag":"2063806042"},"language":"en","primary_location":{"id":"doi:10.1109/icapr.2015.7050701","is_oa":false,"landing_page_url":"http://doi.org/10.1109/icapr.2015.7050701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)","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/A5004667842","display_name":"A Tirumarai Selvan","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A Tirumarai Selvan","raw_affiliation_strings":["V.P. Lab, Dept. of CSE, IIT Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"V.P. Lab, Dept. of CSE, IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069195591","display_name":"Suranjana Samanta","orcid":"https://orcid.org/0000-0002-9958-4258"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suranjana Samanta","raw_affiliation_strings":["V.P. Lab, Dept. of CSE, IIT Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"V.P. Lab, Dept. of CSE, IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000019969","display_name":"Sukhendu Das","orcid":"https://orcid.org/0000-0002-2823-9211"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"education","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sukhendu Das","raw_affiliation_strings":["V.P. Lab, Dept. of CSE, IIT Madras, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"V.P. Lab, Dept. of CSE, IIT Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.04877022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T12676","display_name":"Machine Learning and ELM","score":0.9592000246047974,"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/categorization","display_name":"Categorization","score":0.6722092032432556},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6624448895454407},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6250434517860413},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6186434030532837},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6018778681755066},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.5858889818191528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5666131973266602},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.536113440990448},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.45128777623176575},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.45080631971359253},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.43889111280441284},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.352001428604126},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09930697083473206}],"concepts":[{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.6722092032432556},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6624448895454407},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6250434517860413},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6186434030532837},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6018778681755066},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.5858889818191528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5666131973266602},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.536113440990448},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.45128777623176575},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.45080631971359253},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.43889111280441284},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.352001428604126},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09930697083473206},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icapr.2015.7050701","is_oa":false,"landing_page_url":"http://doi.org/10.1109/icapr.2015.7050701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W46086471","https://openalex.org/W123476658","https://openalex.org/W1576445103","https://openalex.org/W1578862585","https://openalex.org/W1665715489","https://openalex.org/W1722318740","https://openalex.org/W1971221757","https://openalex.org/W1978920452","https://openalex.org/W1981658663","https://openalex.org/W1988348003","https://openalex.org/W2064447488","https://openalex.org/W2099501835","https://openalex.org/W2103851188","https://openalex.org/W2104068492","https://openalex.org/W2111362445","https://openalex.org/W2115191221","https://openalex.org/W2115403315","https://openalex.org/W2119605622","https://openalex.org/W2128053425","https://openalex.org/W2138451337","https://openalex.org/W2149466042","https://openalex.org/W2212660284","https://openalex.org/W4285719527","https://openalex.org/W6601848957","https://openalex.org/W6604957493","https://openalex.org/W6634343353","https://openalex.org/W6637542466","https://openalex.org/W6666709296","https://openalex.org/W6675410418","https://openalex.org/W6677069268","https://openalex.org/W6677430534","https://openalex.org/W6681637710","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W1977009394","https://openalex.org/W3136267388","https://openalex.org/W3186065094","https://openalex.org/W4287263085","https://openalex.org/W3093803318","https://openalex.org/W3204418343","https://openalex.org/W4390401377"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,16,31,38,58,106,126],"method":[4,90,116],"of":[5,12,33,60,95,98,108,117,129],"cross-domain":[6],"object":[7],"categorization,":[8],"using":[9,20,105],"the":[10,23,43,48,51,66,74,78,86,89,92,96,114,130],"concept":[11],"domain":[13,25,119],"adaptation.":[14],"Here,":[15],"classifier":[17],"is":[18,28],"trained":[19],"samples":[21,35],"from":[22,37,76,100],"source/auxiliary":[24],"and":[26],"performance":[27],"observed":[29],"on":[30,65,69],"set":[32],"test":[34],"taken":[36],"different":[39],"domain,":[40,104],"termed":[41],"as":[42],"target":[44,103],"domain.":[45],"To":[46],"overcome":[47],"difference":[49],"between":[50],"two":[52],"domains,":[53],"we":[54],"aim":[55],"to":[56,102],"find":[57],"sequence":[59,107],"optimally":[61],"weighted":[62,109],"sub-spaces,":[63],"lying":[64],"geodesic":[67],"path":[68],"Grassmann":[70],"manifold,":[71],"such":[72],"that":[73,113],"instances":[75],"both":[77],"domains":[79],"follow":[80],"similar":[81],"distributions":[82],"when":[83],"projected":[84],"onto":[85],"sub-spaces.":[87,110],"Hence,":[88],"models":[91],"gradual":[93],"change":[94],"distribution":[97],"data":[99],"source":[101],"Results":[111],"show":[112],"proposed":[115],"unsupervised":[118],"adaptation":[120],"provides":[121],"better":[122],"classification":[123],"accuracy":[124],"than":[125],"few":[127],"state":[128],"art":[131],"methods.":[132]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}