{"id":"https://openalex.org/W4402508548","doi":"https://doi.org/10.1109/access.2024.3459920","title":"Identification of Tailing Ponds From Multi-Source and High-Resolution Remote Sensing Imageries Using Deep Learning-Based Method","display_name":"Identification of Tailing Ponds From Multi-Source and High-Resolution Remote Sensing Imageries Using Deep Learning-Based Method","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402508548","doi":"https://doi.org/10.1109/access.2024.3459920"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3459920","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3459920","pdf_url":null,"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://doi.org/10.1109/access.2024.3459920","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049344506","display_name":"S.R. Ge","orcid":"https://orcid.org/0009-0004-0594-768X"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanfeng Ge","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-0594-768X","affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742507","display_name":"Jingxiang Gao","orcid":"https://orcid.org/0000-0001-7495-7022"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingxiang Gao","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7495-7022","affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108573715","display_name":"Guangqi Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151703","display_name":"China Coal Technology and Engineering Group Corp (China)","ror":"https://ror.org/045d9gj14","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151703"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangqi Cai","raw_affiliation_strings":["China Coal Pingshuo Group Company Ltd., Shuozhou, China","China Coal Pingshuo Group Co., Ltd, Shuozhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Coal Pingshuo Group Company Ltd., Shuozhou, China","institution_ids":["https://openalex.org/I4210151703"]},{"raw_affiliation_string":"China Coal Pingshuo Group Co., Ltd, Shuozhou, China","institution_ids":["https://openalex.org/I4210151703"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781289","display_name":"Weihong Li","orcid":"https://orcid.org/0000-0003-4942-822X"},"institutions":[{"id":"https://openalex.org/I4210151703","display_name":"China Coal Technology and Engineering Group Corp (China)","ror":"https://ror.org/045d9gj14","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210151703"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihong Li","raw_affiliation_strings":["China Coal Pingshuo Group Company Ltd., Shuozhou, China","China Coal Pingshuo Group Co., Ltd, Shuozhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Coal Pingshuo Group Company Ltd., Shuozhou, China","institution_ids":["https://openalex.org/I4210151703"]},{"raw_affiliation_string":"China Coal Pingshuo Group Co., Ltd, Shuozhou, China","institution_ids":["https://openalex.org/I4210151703"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112491998","display_name":"Changhui Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhui Xu","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing, China","Chinese Academy of Surveying &#x0026; Mapping, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing, China","institution_ids":["https://openalex.org/I4210114963"]},{"raw_affiliation_string":"Chinese Academy of Surveying &#x0026; Mapping, Beijing, China","institution_ids":["https://openalex.org/I4210114963"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6901,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64772802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"134568","last_page":"134577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9315000176429749,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9315000176429749,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T12543","display_name":"Groundwater and Watershed Analysis","score":0.9010999798774719,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6706445217132568},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6611665487289429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6386554837226868},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5154648423194885},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4396209418773651},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.42130163311958313},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.243149995803833}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6706445217132568},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6611665487289429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6386554837226868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5154648423194885},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4396209418773651},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.42130163311958313},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.243149995803833},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3459920","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3459920","pdf_url":null,"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:3e8e687213cf4f009b282bc23394cf82","is_oa":true,"landing_page_url":"https://doaj.org/article/3e8e687213cf4f009b282bc23394cf82","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 12, Pp 134568-134577 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3459920","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3459920","pdf_url":null,"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":[],"awards":[{"id":"https://openalex.org/G3240177076","display_name":null,"funder_award_id":"42394060","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5436423936","display_name":null,"funder_award_id":"42394065","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2262752383","https://openalex.org/W2570343428","https://openalex.org/W2801341331","https://openalex.org/W2963037989","https://openalex.org/W2965179263","https://openalex.org/W3018757597","https://openalex.org/W3025007558","https://openalex.org/W3132826520","https://openalex.org/W3158114921","https://openalex.org/W3164449615","https://openalex.org/W3176659256","https://openalex.org/W4200006747","https://openalex.org/W4281698396","https://openalex.org/W4296006148","https://openalex.org/W4297676427","https://openalex.org/W4308379969","https://openalex.org/W4312933394","https://openalex.org/W4322502989","https://openalex.org/W4382119132","https://openalex.org/W4385606539","https://openalex.org/W4386076325","https://openalex.org/W4386602255","https://openalex.org/W4389104786","https://openalex.org/W4392939809","https://openalex.org/W4399496596","https://openalex.org/W6750227808","https://openalex.org/W6802878479"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W2898732673","https://openalex.org/W782553550","https://openalex.org/W2410053581","https://openalex.org/W1987967678","https://openalex.org/W2383658677","https://openalex.org/W3123203398","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2369060955"],"abstract_inverted_index":{"Monitoring":[0],"the":[1,27,70,84,127,134,138,142,151,194,204],"spatial":[2],"distribution":[3],"of":[4,8,30,72,121,144],"tailing":[5,31,41],"ponds":[6,32],"is":[7,20,100],"great":[9],"significance":[10],"for":[11],"environmental":[12],"governance":[13],"in":[14,33,58,176,210],"mining":[15],"areas.":[16,35],"Remote":[17],"sensing":[18,81],"technology":[19],"an":[21,87],"effective":[22],"tool":[23],"to":[24,68],"quickly":[25],"obtain":[26],"location":[28,71],"information":[29,132],"large":[34],"However,":[36],"most":[37],"current":[38],"studies":[39],"about":[40,133],"pond":[42],"detection":[43,56,98,139,171],"focus":[44],"on":[45],"using":[46],"images":[47],"from":[48,76],"single":[49],"sensor":[50],"and":[51,78,114,136,158,166,181],"are":[52],"with":[53,206],"relatively":[54],"low":[55],"accuracy":[57],"complex":[59,211],"backgrounds.":[60,212],"In":[61,83],"this":[62],"paper,":[63],"we":[64],"present":[65],"a":[66,104,109,115,145],"framework":[67],"annotate":[69],"Tailing":[73],"Ponds":[74],"(TPs)":[75],"multi-source":[77],"high-resolution":[79],"remote":[80],"images.":[82],"proposed":[85,195],"framework,":[86],"improved":[88],"You":[89],"Only":[90],"Look":[91],"Once":[92],"(YOLO)":[93],"deep":[94],"learning":[95],"based":[96,169,197],"object":[97,135],"model":[99],"employed,":[101],"which":[102],"embeds":[103],"high-density":[105],"feature":[106,111],"aggregation":[107,112],"module,":[108],"low-parameter":[110],"module":[113],"refined":[116,146],"loss":[117,147],"function.":[118],"The":[119],"introductions":[120],"two":[122],"new":[123],"modules":[124],"can":[125,149,201],"make":[126,150],"network":[128],"better":[129],"capture":[130],"global":[131],"accelerate":[137],"speed,":[140],"while":[141],"introduction":[143],"function":[148],"target":[152],"box":[153],"regression":[154],"process":[155],"more":[156],"robust":[157,167],"avoiding":[159],"divergence":[160],"during":[161],"training.":[162],"To":[163],"train":[164],"reliable":[165],"YOLO":[168,196],"TP":[170,198],"model,":[172],"sufficient":[173],"training":[174],"samples":[175],"different":[177,183],"backgrounds":[178],"were":[179,187],"collected,":[180],"some":[182],"sample":[184],"augmentation":[185],"methods":[186],"also":[188],"employed.":[189],"Experimental":[190],"results":[191],"validate":[192],"that,":[193],"annotation":[199,208],"method":[200],"accurately":[202],"identify":[203],"targets":[205],"high":[207],"accuracies":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
