{"id":"https://openalex.org/W3010936778","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023267","title":"Research on Cloud Recognition Technology Based on Transfer Learning","display_name":"Research on Cloud Recognition Technology Based on Transfer Learning","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3010936778","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023267","mag":"3010936778"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5035872427","display_name":"Chunyao Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunyao Fang","raw_affiliation_strings":["Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008153237","display_name":"Kebin Jia","orcid":"https://orcid.org/0000-0001-7620-2221"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kebin Jia","raw_affiliation_strings":["Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100660888","display_name":"Pengyu Liu","orcid":"https://orcid.org/0000-0002-7198-4102"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengyu Liu","raw_affiliation_strings":["Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100425177","display_name":"Liang Zhang","orcid":"https://orcid.org/0000-0002-1198-5680"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Zhang","raw_affiliation_strings":["Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5035872427"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.3406,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.67087725,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"791","last_page":"796"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9900000095367432,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9900000095367432,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.8338483572006226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6744287610054016},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.610386312007904},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5732713341712952},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5354336500167847},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5104355216026306},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4817776381969452},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4140360355377197},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3447553515434265},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.32067734003067017},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09711527824401855},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07750362157821655}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.8338483572006226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6744287610054016},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.610386312007904},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5732713341712952},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5354336500167847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5104355216026306},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4817776381969452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4140360355377197},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3447553515434265},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.32067734003067017},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09711527824401855},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07750362157821655},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc47483.2019.9023267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/6","score":0.49000000953674316,"display_name":"Clean water and sanitation"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2386516376","https://openalex.org/W2576828326","https://openalex.org/W2741265397","https://openalex.org/W2746211487","https://openalex.org/W2771059075","https://openalex.org/W2800799576","https://openalex.org/W2811124753","https://openalex.org/W2887626628","https://openalex.org/W2921724185","https://openalex.org/W6745946713","https://openalex.org/W7014798534"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2027108423","https://openalex.org/W1855666948","https://openalex.org/W2758561209","https://openalex.org/W2594414941","https://openalex.org/W1548095260","https://openalex.org/W2781711915","https://openalex.org/W2112817590","https://openalex.org/W1555291398"],"abstract_inverted_index":{"The":[0],"cloud":[1,28,35,61],"is":[2,112],"an":[3],"important":[4],"part":[5],"of":[6,26,33,45,80,87],"the":[7,24,31,43,49,59,99,107,119],"earth's":[8],"thermodynamic":[9],"balance":[10],"and":[11,13,48,84,91,118],"water":[12],"air":[14],"cycle.":[15],"At":[16],"present,":[17],"abundant":[18],"achievements":[19,50],"have":[20],"been":[21,39],"made":[22],"in":[23,42],"research":[25],"satellite":[27],"image,":[29],"while":[30],"recognition":[32,120],"ground-based":[34,60],"image":[36],"has":[37],"always":[38],"a":[40],"difficulty":[41],"field":[44],"pattern":[46],"recognition,":[47],"are":[51],"relatively":[52],"limited.":[53],"In":[54],"this":[55,116],"paper,":[56],"based":[57],"on":[58,98],"map":[62],"data":[63,71,101],"set":[64],"provided":[65],"by":[66,78],"standard":[67],"weather":[68],"stations,":[69],"after":[70],"enhancement,":[72],"5":[73,92],"network":[74,82,89,93,110],"models":[75],"were":[76,96],"trained":[77],"means":[79],"fine-tuning":[81],"parameters":[83],"freezing":[85],"weights":[86],"different":[88],"layers,":[90],"migration":[94],"configurations":[95],"used":[97],"enhanced":[100],"set.":[102],"Experimental":[103],"results":[104],"show":[105],"that":[106],"fine-tuned":[108],"Densenet":[109],"model":[111],"more":[113],"suitable":[114],"for":[115],"project,":[117],"accuracy":[121],"can":[122],"reach":[123],"96.55%.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
