{"id":"https://openalex.org/W4404032921","doi":"https://doi.org/10.1109/icccnt61001.2024.10725106","title":"Enhancing Classification Power: Tree Strength-Infused Enriched Random Forest","display_name":"Enhancing Classification Power: Tree Strength-Infused Enriched Random Forest","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4404032921","doi":"https://doi.org/10.1109/icccnt61001.2024.10725106"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt61001.2024.10725106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10725106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5035484504","display_name":"Vikas Jain","orcid":"https://orcid.org/0000-0002-6382-5814"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Vikas Jain","raw_affiliation_strings":["Bennett University,SCSET,Gr. Noida,India"],"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Gr. Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031732855","display_name":"Tej Bahadur Chandra","orcid":"https://orcid.org/0000-0002-3499-3296"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tej Bahadur Chandra","raw_affiliation_strings":["Bennett University,SCSET,Gr. Noida,India"],"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Gr. Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101798557","display_name":"Atul Kumar Srivastava","orcid":"https://orcid.org/0000-0001-7039-7582"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Atul Kumar Srivastava","raw_affiliation_strings":["Bennett University,SCSET,Gr. Noida,India"],"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Gr. Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035484504"],"corresponding_institution_ids":["https://openalex.org/I3129773123"],"apc_list":null,"apc_paid":null,"fwci":0.5248,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67261971,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"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/T10057","display_name":"Face and Expression Recognition","score":0.8331999778747559,"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/T10057","display_name":"Face and Expression Recognition","score":0.8331999778747559,"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/T10320","display_name":"Neural Networks and Applications","score":0.800599992275238,"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/random-forest","display_name":"Random forest","score":0.7732746601104736},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5341794490814209},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5125508308410645},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4457474648952484},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.41370129585266113},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.3615679442882538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3432336151599884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17343702912330627},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07467380166053772},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07214897871017456}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7732746601104736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5341794490814209},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5125508308410645},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4457474648952484},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.41370129585266113},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.3615679442882538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3432336151599884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17343702912330627},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07467380166053772},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07214897871017456},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt61001.2024.10725106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10725106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W137456267","https://openalex.org/W1972450020","https://openalex.org/W1975891294","https://openalex.org/W2036718463","https://openalex.org/W2061438946","https://openalex.org/W2112796928","https://openalex.org/W2140405352","https://openalex.org/W2155904486","https://openalex.org/W2499439150","https://openalex.org/W2746722496","https://openalex.org/W2768149277","https://openalex.org/W2802502226","https://openalex.org/W2919692498","https://openalex.org/W2944517071","https://openalex.org/W2987694862","https://openalex.org/W2990254879","https://openalex.org/W3080833865","https://openalex.org/W3089734353","https://openalex.org/W4282000784","https://openalex.org/W4400762160","https://openalex.org/W6638373262","https://openalex.org/W6676959241","https://openalex.org/W6682020064","https://openalex.org/W6730263737"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487"],"abstract_inverted_index":{"Over":[0],"the":[1,12,71,100,103,112,129,133],"last":[2],"two":[3],"decades,":[4],"Random":[5,76],"forest":[6],"(RF)":[7],"has":[8,22,38,108,135],"been":[9,23,40,109],"one":[10],"of":[11,66,84,102,119,128],"well-known":[13,122],"and":[14,32,90,116,123],"most":[15],"exploited":[16],"ensemble-based":[17],"machine":[18],"learning":[19],"approaches.":[20,142],"It":[21],"used":[24,63],"for":[25],"computer":[26],"vision,":[27],"pattern":[28],"recognition,":[29],"medical":[30],"imaging,":[31],"many":[33],"other":[34,140],"fields.":[35],"However,":[36],"it":[37],"always":[39],"a":[41,55,64,80,96],"challenging":[42],"task":[43],"to":[44,53,69],"come":[45],"up":[46],"with":[47],"an":[48],"approach":[49],"that":[50,132],"will":[51],"lead":[52],"constructing":[54],"more":[56],"reliable":[57],"RF.":[58],"In":[59],"this":[60],"study,":[61],"we":[62],"concept":[65],"tree":[67],"strength":[68],"construct":[70],"RF,":[72],"called":[73],"as":[74,95],"Enriched":[75],"Forest":[77],"(ERF).":[78],"As":[79],"feature":[81,97],"extraction,":[82],"Bag":[83],"Visual":[85],"Words":[86],"(BoVW)":[87],"is":[88],"used,":[89],"Grey":[91],"Wolf":[92],"Optimization":[93],"(GWO)":[94],"selection":[98],"during":[99],"construction":[101],"ERF.":[104],"The":[105,126],"suggested":[106],"method":[107],"evaluated":[110],"using":[111],"MNSIT,":[113],"Caltech-101,":[114],"Caltech-256,":[115],"UCI":[117],"repositories\u2014all":[118],"which":[120],"are":[121],"openly":[124],"accessible.":[125],"outcomes":[127],"experiments":[130],"indicate":[131],"ERF":[134],"achieved":[136],"better":[137],"results":[138],"than":[139],"RF-based":[141]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
