{"id":"https://openalex.org/W4399619894","doi":"https://doi.org/10.1109/tgrs.2024.3413892","title":"CLDiff: Weakly Supervised Cloud Detection With Denoising Diffusion Probabilistic Models","display_name":"CLDiff: Weakly Supervised Cloud Detection With Denoising Diffusion Probabilistic Models","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399619894","doi":"https://doi.org/10.1109/tgrs.2024.3413892"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3413892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3413892","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5020484951","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0003-0010-5200"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Key Laboratory of Big Data and Artificial Intelligence in Transportation, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0010-5200","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data and Artificial Intelligence in Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005350496","display_name":"Qingyong Li","orcid":"https://orcid.org/0000-0002-3860-4809"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyong Li","raw_affiliation_strings":["Key Laboratory of Big Data and Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, and the Frontiers Science Center for Smart High-Speed Railway System, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3860-4809","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data and Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, and the Frontiers Science Center for Smart High-Speed Railway System, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079144613","display_name":"Zhigang Yao","orcid":"https://orcid.org/0000-0002-8034-6524"},"institutions":[{"id":"https://openalex.org/I4210137516","display_name":"Beijing Meteorological Bureau","ror":"https://ror.org/03wd9vk87","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210137516"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Yao","raw_affiliation_strings":["Beijing Institute of Applied Meteorology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Applied Meteorology, Beijing, China","institution_ids":["https://openalex.org/I4210137516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101933866","display_name":"Jun Jiang","orcid":"https://orcid.org/0000-0002-6351-1129"},"institutions":[{"id":"https://openalex.org/I4210137516","display_name":"Beijing Meteorological Bureau","ror":"https://ror.org/03wd9vk87","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210137516"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Jiang","raw_affiliation_strings":["Beijing Institute of Applied Meteorology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Applied Meteorology, Beijing, China","institution_ids":["https://openalex.org/I4210137516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113996279","display_name":"Zhijun Qiu","orcid":"https://orcid.org/0000-0001-6120-3619"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zhijun Qiu","raw_affiliation_strings":["Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0001-6120-3619","affiliations":[{"raw_affiliation_string":"Donadeo Innovation Centre for Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100396367","display_name":"Wen Wang","orcid":"https://orcid.org/0000-0002-6076-9714"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Wang","raw_affiliation_strings":["Key Laboratory of Big Data and Artificial Intelligence in Transportation, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6076-9714","affiliations":[{"raw_affiliation_string":"Key Laboratory of Big Data and Artificial Intelligence in Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5352,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.55693835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9387000203132629,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9387000203132629,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9208999872207642,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9151999950408936,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.7116049528121948},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6247559785842896},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5900868773460388},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5036167502403259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46058860421180725},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4554242491722107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41999661922454834},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0756881833076477}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7116049528121948},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6247559785842896},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5900868773460388},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5036167502403259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46058860421180725},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4554242491722107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41999661922454834},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0756881833076477},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"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/tgrs.2024.3413892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3413892","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G1170972663","display_name":null,"funder_award_id":"2023JBZY037","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G1375215039","display_name":null,"funder_award_id":"62276019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3445688267","display_name":null,"funder_award_id":"2022JBQY007","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G366719221","display_name":null,"funder_award_id":"62306028","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8409179332","display_name":null,"funder_award_id":"U2034211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2028240797","https://openalex.org/W2068124105","https://openalex.org/W2157151912","https://openalex.org/W2194775991","https://openalex.org/W2584156879","https://openalex.org/W2605847660","https://openalex.org/W2771508394","https://openalex.org/W2784782871","https://openalex.org/W2788309473","https://openalex.org/W2901249518","https://openalex.org/W2910101086","https://openalex.org/W2927122915","https://openalex.org/W2946072066","https://openalex.org/W2950314938","https://openalex.org/W2982092116","https://openalex.org/W3080368312","https://openalex.org/W3098834274","https://openalex.org/W3129390331","https://openalex.org/W3138074985","https://openalex.org/W3138516171","https://openalex.org/W3173374491","https://openalex.org/W3194376449","https://openalex.org/W3210827952","https://openalex.org/W4205510142","https://openalex.org/W4224028831","https://openalex.org/W4283760989","https://openalex.org/W4285207472","https://openalex.org/W4285302592","https://openalex.org/W4292702164","https://openalex.org/W4292829030","https://openalex.org/W4300973224","https://openalex.org/W4313139852","https://openalex.org/W4313524854","https://openalex.org/W4313525856","https://openalex.org/W4319300975","https://openalex.org/W4321484009","https://openalex.org/W4360884927","https://openalex.org/W4366310757","https://openalex.org/W4383428058","https://openalex.org/W4384080234","https://openalex.org/W4386066092","https://openalex.org/W4386083151","https://openalex.org/W4386113271","https://openalex.org/W4386352882","https://openalex.org/W4387211418","https://openalex.org/W4389328551","https://openalex.org/W4390872147","https://openalex.org/W4392719543","https://openalex.org/W6637373629","https://openalex.org/W6679045638","https://openalex.org/W6718379498","https://openalex.org/W6745560452","https://openalex.org/W6778946027","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6788990321","https://openalex.org/W6805335523","https://openalex.org/W6805547681","https://openalex.org/W6838327568","https://openalex.org/W6843976751","https://openalex.org/W6845888603","https://openalex.org/W6846611385"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W3150465815","https://openalex.org/W1997222214","https://openalex.org/W2802581102","https://openalex.org/W4205786897"],"abstract_inverted_index":{"Cloud":[0],"detection":[1,21,41,53],"is":[2,91,126,216],"an":[3],"essential":[4],"step":[5],"in":[6,98,113,135,194,205,214],"remote":[7],"sensing":[8],"(RS)":[9],"image":[10],"processing,":[11],"contributing":[12],"to":[13,93,128,150,167,176],"various":[14],"applications.":[15],"However,":[16],"existing":[17],"fully":[18],"supervised":[19,39],"cloud":[20,40,52,141,153,178],"methods":[22],"rely":[23],"on":[24,78],"massive":[25],"pixel-wise":[26],"annotations,":[27],"which":[28,58],"are":[29],"expensive":[30],"and":[31,107,155,184],"time-consuming.":[32],"To":[33,67],"alleviate":[34],"the":[35,79,99,114,130,169,186],"annotation":[36],"burden,":[37],"weakly":[38],"(WSCD)":[42],"has":[43],"received":[44],"extensive":[45],"attention":[46],"recently.":[47],"One":[48],"standard":[49],"approach":[50,173],"performs":[51],"within":[54],"a":[55,73,85,102,123,136,146],"classification":[56],"paradigm,":[57],"inevitably":[59],"faces":[60],"category":[61],"ambiguity":[62],"when":[63],"detecting":[64],"semitransparent":[65,157],"clouds.":[66,158],"tackle":[68],"this":[69,212],"problem,":[70],"we":[71],"propose":[72],"novel":[74],"WSCD":[75],"framework":[76],"based":[77],"diffusion":[80,124,170],"model,":[81],"termed":[82],"CLDiff.":[83],"Specifically,":[84],"multiscale":[86,95],"feature":[87],"rectification":[88],"(MFR)":[89],"module":[90],"introduced":[92],"extract":[94],"semantic":[96,165,182,190],"features":[97],"encoder,":[100],"enabling":[101],"definite":[103,181],"identification":[104],"of":[105,133,211],"clouds":[106,118,134],"mitigating":[108],"interference":[109],"from":[110],"bright":[111],"objects":[112],"background.":[115],"Considering":[116],"that":[117,200],"exhibit":[119],"varying":[120],"optical":[121],"thicknesses,":[122],"decoder":[125],"developed":[127],"model":[129],"intraclass":[131],"variations":[132],"generative":[137],"strategy,":[138],"improving":[139],"thin":[140],"detection.":[142],"Initially,":[143],"it":[144],"devises":[145],"Gaussian":[147],"modulation":[148],"function":[149],"recalibrate":[151],"ambiguous":[152],"activations":[154,162],"emphasize":[156],"Subsequently,":[159],"these":[160],"modulated":[161],"serve":[163],"as":[164,192],"guidance":[166],"optimize":[168],"process.":[171],"This":[172],"enables":[174],"CLDiff":[175,201],"activate":[177],"contours":[179],"under":[180],"conditions":[183],"avoids":[185],"additional":[187],"branches":[188],"for":[189],"learning":[191],"found":[193],"previous":[195],"methods.":[196],"Experimental":[197],"results":[198],"demonstrate":[199],"achieves":[202],"state-of-the-art":[203],"performance":[204],"WSCD.":[206],"A":[207],"public":[208],"reference":[209],"implementation":[210],"work":[213],"PyTorch":[215],"available":[217],"athttps://github.com/YLiu-creator/CLDiff.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}