{"id":"https://openalex.org/W2125094180","doi":"https://doi.org/10.1109/cvpr.2010.5540055","title":"Far-sighted active learning on a budget for image and video recognition","display_name":"Far-sighted active learning on a budget for image and video recognition","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2125094180","doi":"https://doi.org/10.1109/cvpr.2010.5540055","mag":"2125094180"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5540055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","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/A5011416719","display_name":"Sudheendra Vijayanarasimhan","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sudheendra Vijayanarasimhan","raw_affiliation_strings":["University of Texas, Austin, USA","University of Texas at Austin#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Texas, Austin, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin#TAB#","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101633144","display_name":"Prateek Jain","orcid":"https://orcid.org/0000-0002-9233-5160"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prateek Jain","raw_affiliation_strings":["University of Texas, Austin, USA","University of Texas at Austin#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Texas, Austin, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin#TAB#","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012765543","display_name":"Kristen Grauman","orcid":"https://orcid.org/0000-0002-9591-5873"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kristen Grauman","raw_affiliation_strings":["University of Texas, Austin, USA","University of Texas at Austin#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Texas, Austin, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"University of Texas at Austin#TAB#","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011416719"],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":13.4704,"has_fulltext":false,"cited_by_count":85,"citation_normalized_percentile":{"value":0.98805373,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3035","last_page":"3042"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.986299991607666,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9847999811172485,"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/computer-science","display_name":"Computer science","score":0.8385298848152161},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.6422543525695801},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6334908604621887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5347871780395508},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5232731103897095},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46540170907974243},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46404239535331726},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45527926087379456},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44427937269210815},{"id":"https://openalex.org/keywords/budget-constraint","display_name":"Budget constraint","score":0.41645291447639465},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4153420329093933},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32558465003967285}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8385298848152161},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.6422543525695801},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6334908604621887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347871780395508},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5232731103897095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46540170907974243},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46404239535331726},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45527926087379456},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44427937269210815},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.41645291447639465},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4153420329093933},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32558465003967285},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C133425853","wikidata":"https://www.wikidata.org/wiki/Q60571","display_name":"Neoclassical economics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2010.5540055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.299.3518","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.299.3518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.utexas.edu/~grauman/papers/vijayanarasimhan_cvpr2010.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.330.7000","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.7000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.utexas.edu/~svnaras/papers/vijayanarasimhan_cvpr2010.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W5526034","https://openalex.org/W138745945","https://openalex.org/W1483816357","https://openalex.org/W1514940655","https://openalex.org/W1515450954","https://openalex.org/W1519196800","https://openalex.org/W1528361845","https://openalex.org/W1739260168","https://openalex.org/W1845402413","https://openalex.org/W1977612207","https://openalex.org/W1979412670","https://openalex.org/W2016405781","https://openalex.org/W2021774297","https://openalex.org/W2095729244","https://openalex.org/W2101825085","https://openalex.org/W2102162869","https://openalex.org/W2107008379","https://openalex.org/W2108598243","https://openalex.org/W2109832419","https://openalex.org/W2118073957","https://openalex.org/W2118236796","https://openalex.org/W2137795521","https://openalex.org/W2140539195","https://openalex.org/W2142194269","https://openalex.org/W2148029428","https://openalex.org/W2149489787","https://openalex.org/W2903158431","https://openalex.org/W4239072543","https://openalex.org/W4285719527","https://openalex.org/W6600243474","https://openalex.org/W6605658577","https://openalex.org/W6628964739","https://openalex.org/W6630965568","https://openalex.org/W6637774275","https://openalex.org/W6638701278","https://openalex.org/W6644536952","https://openalex.org/W6654641199","https://openalex.org/W6675206559","https://openalex.org/W6676132248","https://openalex.org/W6676257810","https://openalex.org/W6676297131","https://openalex.org/W6680113041","https://openalex.org/W6756615331"],"related_works":["https://openalex.org/W2081982437","https://openalex.org/W4394857231","https://openalex.org/W2027050655","https://openalex.org/W3028244590","https://openalex.org/W4254349500","https://openalex.org/W2014369232","https://openalex.org/W3122042562","https://openalex.org/W2050078012","https://openalex.org/W2060761133","https://openalex.org/W2360307734"],"abstract_inverted_index":{"Active":[0],"learning":[1],"methods":[2,36],"aim":[3],"to":[4,11,17,86,113,129],"select":[5,64],"the":[6,24,54,60,76,81,92,111,114,119,131,135,138,145],"most":[7,28,34],"informative":[8],"unlabeled":[9],"instances":[10],"label":[12,44],"first,":[13],"and":[14,156,159,169],"can":[15],"help":[16],"focus":[18],"image":[19],"or":[20],"video":[21],"annotations":[22],"on":[23,88,148],"examples":[25,68,140],"that":[26,137],"will":[27,141],"improve":[29],"a":[30,42,46,65,70,97],"recognition":[31],"system.":[32],"However,":[33],"existing":[35],"only":[37],"make":[38],"myopic":[39],"queries":[40,108],"for":[41,151],"single":[43],"at":[45,49,57],"time,":[47],"retraining":[48],"each":[50,58],"iteration.":[51],"We":[52,90,143],"consider":[53],"problem":[55,100],"where":[56,75,101],"iteration":[59],"active":[61],"learner":[62],"must":[63],"set":[66],"of":[67,73,106],"meeting":[69],"given":[71],"budget":[72,77],"supervision,":[74],"is":[78],"determined":[79],"by":[80],"funds":[82],"(or":[83],"time)":[84],"available":[85],"spend":[87],"annotation.":[89],"formulate":[91],"budgeted":[93],"selection":[94,171],"task":[95],"as":[96],"continuous":[98],"optimization":[99],"we":[102,126,160],"determine":[103],"which":[104],"subset":[105],"possible":[107],"should":[109],"maximize":[110],"improvement":[112],"classifier's":[115],"objective,":[116],"without":[117],"overspending":[118],"budget.":[120],"To":[121],"ensure":[122],"far-sighted":[123],"batch":[124,170],"requests,":[125],"show":[127,161],"how":[128],"incorporate":[130],"predicted":[132],"change":[133],"in":[134],"model":[136],"candidate":[139],"induce.":[142],"demonstrate":[144],"proposed":[146],"algorithm":[147],"three":[149],"datasets":[150],"object":[152],"recognition,":[153,155],"activity":[154],"content-based":[157],"retrieval,":[158],"its":[162],"clear":[163],"practical":[164],"advantages":[165],"over":[166],"random,":[167],"myopic,":[168],"baselines.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}