{"id":"https://openalex.org/W2944899677","doi":"https://doi.org/10.1109/access.2019.2916905","title":"Dual Guided Loss for Ground-Based Cloud Classification in Weather Station Networks","display_name":"Dual Guided Loss for Ground-Based Cloud Classification in Weather Station Networks","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2944899677","doi":"https://doi.org/10.1109/access.2019.2916905","mag":"2944899677"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2916905","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2916905","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08715352.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08715352.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100331912","display_name":"Mei Li","orcid":"https://orcid.org/0000-0002-5814-6091"},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mei Li","raw_affiliation_strings":["Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319110","display_name":"Shuang Liu","orcid":"https://orcid.org/0000-0002-9027-0690"},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Liu","raw_affiliation_strings":["Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-9027-0690","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100350965","display_name":"Zhong Zhang","orcid":"https://orcid.org/0000-0002-2993-8612"},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Zhang","raw_affiliation_strings":["Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-2993-8612","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China","institution_ids":["https://openalex.org/I15062923"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100331912"],"corresponding_institution_ids":["https://openalex.org/I15062923"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4288,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.85374616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"63081","last_page":"63088"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9990000128746033,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9990000128746033,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9954000115394592,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9948999881744385,"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/discriminative-model","display_name":"Discriminative model","score":0.7319307327270508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7171587347984314},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6728067398071289},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6522901058197021},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.551442563533783},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5277312994003296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5144577026367188},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47529566287994385},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.436809241771698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.347744345664978},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32470762729644775}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7319307327270508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7171587347984314},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6728067398071289},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6522901058197021},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.551442563533783},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5277312994003296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5144577026367188},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47529566287994385},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.436809241771698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.347744345664978},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32470762729644775},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2916905","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2916905","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08715352.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d11b79abf17746c39cb38899525a39cd","is_oa":true,"landing_page_url":"https://doaj.org/article/d11b79abf17746c39cb38899525a39cd","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 63081-63088 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2916905","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2916905","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08715352.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.699999988079071,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1896112739","display_name":null,"funder_award_id":"17JCZDJC30600","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G248294826","display_name":null,"funder_award_id":"61711530240","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2984157084","display_name":null,"funder_award_id":"61501327","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3878003079","display_name":null,"funder_award_id":"201800002","funder_id":"https://openalex.org/F4320326873","funder_display_name":"National Laboratory of Pattern Recognition"},{"id":"https://openalex.org/G3908059555","display_name":null,"funder_award_id":"135202RC1703","funder_id":"https://openalex.org/F4320324792","funder_display_name":"Tianjin Normal University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null},{"id":"https://openalex.org/F4320324792","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559"},{"id":"https://openalex.org/F4320326873","display_name":"National Laboratory of Pattern Recognition","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2944899677.pdf","grobid_xml":"https://content.openalex.org/works/W2944899677.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1625255723","https://openalex.org/W1852802191","https://openalex.org/W1878216218","https://openalex.org/W1981121910","https://openalex.org/W2002538582","https://openalex.org/W2028451171","https://openalex.org/W2096733369","https://openalex.org/W2114640875","https://openalex.org/W2138621090","https://openalex.org/W2147141800","https://openalex.org/W2151103935","https://openalex.org/W2153462159","https://openalex.org/W2162915993","https://openalex.org/W2163352848","https://openalex.org/W2190068738","https://openalex.org/W2194775991","https://openalex.org/W2292095125","https://openalex.org/W2294272738","https://openalex.org/W2558661413","https://openalex.org/W2602844676","https://openalex.org/W2733849967","https://openalex.org/W2766557427","https://openalex.org/W2791887703","https://openalex.org/W2791901417","https://openalex.org/W2797799020","https://openalex.org/W2798757724","https://openalex.org/W2803345276","https://openalex.org/W2887626628","https://openalex.org/W2888568221","https://openalex.org/W2889065492","https://openalex.org/W2889170399","https://openalex.org/W2891238898","https://openalex.org/W2904872227","https://openalex.org/W2921683268","https://openalex.org/W6636494156"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"In":[0],"this":[1,50],"paper,":[2],"we":[3,52],"propose":[4],"a":[5,54,71],"novel":[6],"loss":[7,11],"function":[8],"named":[9],"dual-guided":[10],"(DGL)":[12],"for":[13],"ground-based":[14,45,67,110],"cloud":[15,46,68,111],"classification":[16],"in":[17,34],"weather":[18],"station":[19],"networks.":[20],"The":[21],"proposed":[22,102],"DGL":[23,103,119],"could":[24],"integrate":[25],"the":[26,35,41,58,65,73,88,91,98,101,105,114,118,121],"knowledge":[27],"of":[28,37,44,90,100,117],"different":[29],"convolutional":[30],"neural":[31],"networks":[32],"(CNNs)":[33],"process":[36],"optimization,":[38],"which":[39,60],"improves":[40],"discriminative":[42],"ability":[43],"feature":[47],"representations.":[48],"To":[49],"end,":[51],"add":[53],"modulation":[55],"term":[56],"into":[57],"DGL,":[59],"assigns":[61],"large":[62],"weights":[63],"to":[64,78,82],"hard-classified":[66,84],"samples.":[69],"As":[70],"result,":[72],"deep":[74,92],"network":[75,93],"is":[76],"forced":[77],"pay":[79],"more":[80],"attention":[81],"these":[83],"samples,":[85],"and":[86,113],"therefore,":[87],"performance":[89],"gets":[94],"improved.":[95],"We":[96],"demonstrate":[97],"effectiveness":[99],"with":[104],"extensive":[106],"experiments":[107],"on":[108],"two":[109],"datasets,":[112],"experimental":[115],"results":[116],"outperform":[120],"state-of-the-art":[122],"methods.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}