{"id":"https://openalex.org/W4409537080","doi":"https://doi.org/10.1109/icvisp64524.2024.10959396","title":"Recognition of Local Bird Species of Yunnan Using Transfer Learning Based on ResNet","display_name":"Recognition of Local Bird Species of Yunnan Using Transfer Learning Based on ResNet","publication_year":2024,"publication_date":"2024-12-27","ids":{"openalex":"https://openalex.org/W4409537080","doi":"https://doi.org/10.1109/icvisp64524.2024.10959396"},"language":"en","primary_location":{"id":"doi:10.1109/icvisp64524.2024.10959396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp64524.2024.10959396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Vision, Image and Signal Processing (ICVISP)","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/A5075505791","display_name":"Wei Yang","orcid":"https://orcid.org/0000-0002-7826-5629"},"institutions":[{"id":"https://openalex.org/I4210144930","display_name":"Baoshan College","ror":"https://ror.org/04t69c375","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210144930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Yang","raw_affiliation_strings":["College of Big Data, BaoShan University,BaoShan,China"],"affiliations":[{"raw_affiliation_string":"College of Big Data, BaoShan University,BaoShan,China","institution_ids":["https://openalex.org/I4210144930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5075505791"],"corresponding_institution_ids":["https://openalex.org/I4210144930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24864417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10199","display_name":"Wildlife Ecology and Conservation","score":0.85589998960495,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T10199","display_name":"Wildlife Ecology and Conservation","score":0.85589998960495,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T12467","display_name":"Rangeland Management and Livestock Ecology","score":0.757099986076355,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/T11665","display_name":"Animal Vocal Communication and Behavior","score":0.7070000171661377,"subfield":{"id":"https://openalex.org/subfields/1309","display_name":"Developmental Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.8684567213058472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5692882537841797},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5652139186859131},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4344680905342102},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2041187286376953}],"concepts":[{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.8684567213058472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5692882537841797},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5652139186859131},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4344680905342102},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2041187286376953}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icvisp64524.2024.10959396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp64524.2024.10959396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Vision, Image and Signal Processing (ICVISP)","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":11,"referenced_works":["https://openalex.org/W2026430219","https://openalex.org/W2123712097","https://openalex.org/W2161381512","https://openalex.org/W2194775991","https://openalex.org/W2952139439","https://openalex.org/W3176923149","https://openalex.org/W3185015140","https://openalex.org/W4312873100","https://openalex.org/W6637373629","https://openalex.org/W6682132143","https://openalex.org/W6796415881"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2599472179","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W3179744494","https://openalex.org/W4362670567","https://openalex.org/W2882771868","https://openalex.org/W4224930320"],"abstract_inverted_index":{"This":[0,97],"study":[1,47,98],"created":[2],"the":[3,15,32,46,52,100,112,126],"GMBID":[4],"dataset":[5],"for":[6,147],"locally":[7],"protected":[8],"bird":[9,115],"species":[10],"in":[11,37,107,111],"Yunnan":[12],"and":[13,43,63,79,117,134],"explored":[14],"application":[16],"of":[17,34,39,103,114],"transfer":[18,105,136],"learning":[19,106,137],"with":[20,129],"different":[21],"ResNet":[22],"architectures":[23],"(ResNet18,":[24],"ResNet34,":[25],"ResNet50)":[26],"on":[27,124],"this":[28],"dataset.":[29],"By":[30],"comparing":[31],"performance":[33,73,93],"these":[35],"models":[36],"terms":[38],"accuracy,":[40,60],"precision,":[41],"recall,":[42],"F1":[44],"score,":[45],"found":[48],"that":[49],"ResNet34":[50,76],"performed":[51],"best,":[53],"achieving":[54],"a":[55,69],"good":[56],"balance":[57],"between":[58],"high":[59],"model":[61,132,142],"complexity,":[62],"computational":[64,83],"efficiency.":[65],"Although":[66],"ResNet50":[67],"has":[68],"deeper":[70],"architecture,":[71],"its":[72],"improvement":[74],"over":[75],"was":[77],"limited,":[78],"it":[80],"incurred":[81],"higher":[82],"costs.":[84],"ResNet18,":[85],"while":[86],"training":[87],"faster,":[88],"had":[89],"slightly":[90],"lower":[91],"overall":[92],"compared":[94],"to":[95,139],"ResNet34.":[96],"highlights":[99],"practical":[101],"significance":[102],"applying":[104],"data-scarce":[108],"regions,":[109],"particularly":[110],"fields":[113],"conservation":[116],"ecological":[118],"monitoring.":[119],"Future":[120],"work":[121],"could":[122],"focus":[123],"expanding":[125],"dataset,":[127],"experimenting":[128],"more":[130],"advanced":[131],"architectures,":[133],"optimizing":[135],"strategies":[138],"further":[140],"enhance":[141],"performance,":[143],"providing":[144],"technical":[145],"support":[146],"wildlife":[148],"conservation.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}