{"id":"https://openalex.org/W2554610697","doi":"https://doi.org/10.1109/mlsp.2016.7738876","title":"Active object detection on graphs via locally informative trees","display_name":"Active object detection on graphs via locally informative trees","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2554610697","doi":"https://doi.org/10.1109/mlsp.2016.7738876","mag":"2554610697"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5055433560","display_name":"Daphney\u2013Stavroula Zois","orcid":"https://orcid.org/0000-0002-7807-7142"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daphney-Stavroula Zois","raw_affiliation_strings":["Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044844161","display_name":"Maxim Raginsky","orcid":"https://orcid.org/0000-0002-5586-9219"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maxim Raginsky","raw_affiliation_strings":["Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.2013,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55739725,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9959999918937683,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9959999918937683,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9878000020980835,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9861000180244446,"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/graph","display_name":"Graph","score":0.5598118305206299},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5549825429916382},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4758952856063843},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47217077016830444},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47015050053596497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4679269790649414},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.45043352246284485},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4203372299671173},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.37676531076431274},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36689430475234985},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34987151622772217},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32355836033821106}],"concepts":[{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5598118305206299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5549825429916382},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4758952856063843},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47217077016830444},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47015050053596497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4679269790649414},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.45043352246284485},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4203372299671173},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.37676531076431274},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36689430475234985},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34987151622772217},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32355836033821106}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2016.7738876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W639708223","https://openalex.org/W1511986666","https://openalex.org/W1837434264","https://openalex.org/W1930392762","https://openalex.org/W1999120268","https://openalex.org/W2031489346","https://openalex.org/W2051192553","https://openalex.org/W2068730032","https://openalex.org/W2088049833","https://openalex.org/W2099111195","https://openalex.org/W2102605133","https://openalex.org/W2137906383","https://openalex.org/W2183235533","https://openalex.org/W2478708596","https://openalex.org/W2951638509","https://openalex.org/W2953106684","https://openalex.org/W2963423396","https://openalex.org/W2963790522","https://openalex.org/W6600313631","https://openalex.org/W6620707391","https://openalex.org/W6638561857","https://openalex.org/W6675026286","https://openalex.org/W6688076771"],"related_works":["https://openalex.org/W4229078645","https://openalex.org/W1977345676","https://openalex.org/W4282032776","https://openalex.org/W2047552823","https://openalex.org/W4321606905","https://openalex.org/W3130445735","https://openalex.org/W2105110616","https://openalex.org/W2747930654","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Active":[0],"object":[1,30],"detection":[2,31],"refers":[3],"to":[4,26],"the":[5,9,24,76,116,131],"problem":[6],"of":[7,13,23,99,115,130],"determining":[8],"existence":[10],"and":[11,41],"location":[12],"objects":[14],"in":[15,46,125],"an":[16,29,80,88],"image":[17,25,37],"by":[18,87],"actively":[19],"selecting":[20],"which":[21],"regions":[22,38,133],"explore.":[27],"Herein,":[28],"algorithm":[32,93,118],"is":[33,52,119,134],"proposed":[34,117],"that":[35,60,72],"models":[36],"as":[39,44,62,105,109],"vertices":[40,56,84],"overlap":[42],"relationships":[43],"edges":[45,59],"a":[47,110],"directed":[48],"weighted":[49],"graph.":[50],"Information":[51],"propagated":[53],"from":[54,75],"labeled":[55],"through":[57],"graph":[58,78],"operate":[61],"noisy":[63],"channels":[64],"via":[65],"message":[66],"passing":[67],"over":[68],"locally":[69],"informative":[70],"trees":[71],"are":[73,85],"extracted":[74],"original":[77],"using":[79],"information-theoretic":[81],"criterion.":[82],"Influential":[83],"determined":[86],"appropriate":[89],"centrality":[90],"index.":[91],"Our":[92],"can":[94],"be":[95],"applied":[96],"on":[97,121],"top":[98],"any":[100],"state-of-the-art":[101],"region":[102],"proposal":[103],"method":[104],"it":[106,108],"treats":[107],"black":[111],"box.":[112],"The":[113],"effectiveness":[114],"illustrated":[120],"different":[122],"scenarios,":[123],"where":[124],"some":[126],"cases":[127],"only":[128],"0.45%":[129],"total":[132],"evaluated.":[135]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}