iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.1109/IGARSS39084.2020.9324647
{"id":"https://openalex.org/W3131906629","doi":"https://doi.org/10.1109/igarss39084.2020.9324647","title":"Super-Resolution of Remote Sensing Images based on a Deep Plug-and-Play Framework","display_name":"Super-Resolution of Remote Sensing Images based on a Deep Plug-and-Play Framework","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3131906629","doi":"https://doi.org/10.1109/igarss39084.2020.9324647","mag":"3131906629"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324647","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5065454973","display_name":"Hongyuan Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongyuan Tao","raw_affiliation_strings":["School of Software Sichuan University,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"School of Software Sichuan University,Chengdu,China","institution_ids":["https://openalex.org/I24185976"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5065454973"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.226,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.433429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":77,"max":79},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Single Image Super-Resolution Techniques","score":0.9999,"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/T11105","display_name":"Single Image Super-Resolution Techniques","score":0.9999,"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":"Multispectral and Hyperspectral Image Fusion","score":0.9976,"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/T10531","display_name":"Stereo Vision and Depth Estimation","score":0.9975,"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/deblurring","display_name":"Deblurring","score":0.8090991},{"id":"https://openalex.org/keywords/super-resolution","display_name":"Super-Resolution","score":0.61557},{"id":"https://openalex.org/keywords/sparse-representations","display_name":"Sparse Representations","score":0.512641},{"id":"https://openalex.org/keywords/depth-estimation","display_name":"Depth Estimation","score":0.502767}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8090991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7371619},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6023067},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5874497},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5625351},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5224413},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.49340978},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4771668},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.47493392},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46543896},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4102624},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3905503},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2092621},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17996418},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09483153},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324647","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.82}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":11,"referenced_works":["https://openalex.org/W1980038761","https://openalex.org/W2242218935","https://openalex.org/W2476548250","https://openalex.org/W2866634454","https://openalex.org/W2907551576","https://openalex.org/W2963470893","https://openalex.org/W2963704386","https://openalex.org/W2963774720","https://openalex.org/W2964951804","https://openalex.org/W2969937244","https://openalex.org/W54257720"],"related_works":["https://openalex.org/W791927757","https://openalex.org/W3207832039","https://openalex.org/W3153582293","https://openalex.org/W3080537281","https://openalex.org/W2905397092","https://openalex.org/W2289746762","https://openalex.org/W2269775642","https://openalex.org/W2182590612","https://openalex.org/W2140617750","https://openalex.org/W2031788393"],"abstract_inverted_index":{"Single":[0],"image":[1,46],"super-resolution":[2],"(SISR)":[3],"based":[4],"on":[5,152],"deep":[6,62,85,107],"neural":[7],"network":[8],"(DNN)":[9],"has":[10],"been":[11],"widely":[12],"studied":[13],"in":[14],"recent":[15],"years":[16],"as":[17,129],"a":[18,42,48,61,84,89,106,121,137],"crucial":[19,131],"technique":[20],"for":[21,133],"remote":[22],"sensing":[23],"(RS)":[24],"applications.":[25],"However,":[26],"owing":[27],"to":[28,40,98,110,144],"the":[29,93,112,130,134,146,149],"complexity":[30],"and":[31,136],"diversity":[32],"of":[33,139,148],"ground":[34],"objects,":[35],"there":[36],"remains":[37],"fundamental":[38],"challenges":[39],"reconstruct":[41,70],"high-resolution":[43],"(HS)":[44],"RS":[45,51,73,153],"from":[47,75,92],"low-resolution":[49],"(LR)":[50],"image,":[52],"especially":[53],"with":[54,79,120],"blur.":[55],"In":[56],"this":[57],"paper,":[58],"I":[59,104],"propose":[60],"plug-and-play":[63,86,108],"residual":[64],"network,":[65],"namely":[66],"DPSRResNet,":[67],"which":[68,115],"can":[69],"high-quality":[71],"HR":[72],"images":[74,78],"LR":[76],"SR":[77],"Gaussian":[80],"blur":[81],"kernels":[82],"via":[83],"framework.":[87],"Specifically,":[88],"degradation":[90],"model":[91],"DPSR":[94],"framework":[95],"is":[96,127],"given":[97],"utilize":[99],"matured":[100],"deblurring":[101],"methods.":[102],"Moreover,":[103],"adopt":[105],"algorithm":[109],"optimize":[111],"energy":[113],"function,":[114],"allows":[116],"plugging":[117],"any":[118],"super-resolver":[119,132],"prior":[122],"term.":[123],"The":[124],"proposed":[125,150],"DPSRResNet":[126],"used":[128],"framework,":[135],"series":[138],"experimental":[140],"results":[141],"are":[142],"presented":[143],"demonstrate":[145],"effectiveness":[147],"method":[151],"images.":[154]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3131906629","counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2024-11-26T02:44:42.450663","created_date":"2021-03-01"}