{"id":"https://openalex.org/W1937766607","doi":"https://doi.org/10.1109/cvpr.2015.7298672","title":"Global refinement of random forest","display_name":"Global refinement of random forest","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1937766607","doi":"https://doi.org/10.1109/cvpr.2015.7298672","mag":"1937766607"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7298672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5100824251","display_name":"Shaoqing Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaoqing Ren","raw_affiliation_strings":["University of Science and Technology of China","University of Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040475616","display_name":"Xudong Cao","orcid":"https://orcid.org/0000-0003-4761-693X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Cao","raw_affiliation_strings":["University of Science and Technology of China","University of Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101959185","display_name":"Yichen Wei","orcid":"https://orcid.org/0009-0003-4327-8459"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Yichen Wei","raw_affiliation_strings":["Microsoft Research","Microsoft Research,USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research,USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037419606","display_name":"Jian Sun","orcid":"https://orcid.org/0000-0001-7206-0641"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Jian Sun","raw_affiliation_strings":["Microsoft Research","Microsoft Research,USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research,USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100824251"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":6.0701,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.96098913,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"723","last_page":"730"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9919000267982483,"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/T11880","display_name":"Forest ecology and management","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/2309","display_name":"Nature and Landscape Conservation"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.5883956551551819},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5246713161468506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20326733589172363}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5883956551551819},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5246713161468506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20326733589172363}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7298672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.700.5234","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.700.5234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://home.ustc.edu.cn/%7Esqren/RefineRF/ImprovingRF_cvpr2015.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W13188192","https://openalex.org/W85229681","https://openalex.org/W1497261839","https://openalex.org/W1568207135","https://openalex.org/W1600199800","https://openalex.org/W1678356000","https://openalex.org/W1713158786","https://openalex.org/W1974614303","https://openalex.org/W1974744233","https://openalex.org/W1980454827","https://openalex.org/W1994635760","https://openalex.org/W1998294030","https://openalex.org/W2009088607","https://openalex.org/W2034489756","https://openalex.org/W2036565334","https://openalex.org/W2058224795","https://openalex.org/W2097523548","https://openalex.org/W2104170135","https://openalex.org/W2104266970","https://openalex.org/W2107285841","https://openalex.org/W2114588272","https://openalex.org/W2118585731","https://openalex.org/W2118664399","https://openalex.org/W2129587342","https://openalex.org/W2135931458","https://openalex.org/W2137502329","https://openalex.org/W2142406598","https://openalex.org/W2146656095","https://openalex.org/W2149706766","https://openalex.org/W2153635508","https://openalex.org/W2156909104","https://openalex.org/W2172156083","https://openalex.org/W2911964244","https://openalex.org/W4213265195","https://openalex.org/W4230674625","https://openalex.org/W4236137412","https://openalex.org/W4293171766","https://openalex.org/W6603471097","https://openalex.org/W6637757873","https://openalex.org/W6674809721","https://openalex.org/W6675679986","https://openalex.org/W6677656871","https://openalex.org/W6680462727"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W2390279801","https://openalex.org/W1924178503"],"abstract_inverted_index":{"Random":[0],"forest":[1,101],"is":[2,38,90,102,108],"well":[3,91,116],"known":[4],"as":[5,115,117,131],"one":[6],"of":[7,14,74,99],"the":[8,23,31,35,48,71,84,96,100,112,118],"best":[9],"learning":[10,25],"methods.":[11],"In":[12,93],"spite":[13],"its":[15],"great":[16],"success,":[17],"it":[18],"also":[19],"has":[20,124],"certain":[21],"drawbacks:":[22],"heuristic":[24],"rule":[26],"does":[27],"not":[28],"effectively":[29],"minimize":[30],"global":[32,54,57,67,79,106],"training":[33],"loss;":[34],"model":[36,113,123],"size":[37,114],"usually":[39],"too":[40],"large":[41],"for":[42],"many":[43],"real":[44],"applications.":[45],"To":[46],"address":[47],"issues,":[49],"we":[50],"propose":[51],"two":[52],"techniques,":[53],"refinement":[55,68],"and":[56,127],"pruning,":[58],"to":[59,110],"improve":[60],"a":[61,78],"pre-trained":[62],"random":[63],"forest.":[64],"The":[65,105,121],"proposed":[66],"jointly":[69],"relearns":[70],"leaf":[72],"nodes":[73],"all":[75],"trees":[76,89],"under":[77],"objective":[80],"function":[81],"so":[82],"that":[83],"complementary":[85],"information":[86],"between":[87],"multiple":[88],"exploited.":[92],"this":[94],"way,":[95],"fitting":[97],"power":[98],"significantly":[103],"enhanced.":[104],"pruning":[107],"developed":[109],"reduce":[111],"over-fitting":[119],"risk.":[120],"refined":[122],"better":[125],"performance":[126],"smaller":[128],"storage":[129],"cost,":[130],"verified":[132],"in":[133],"extensive":[134],"experiments.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}