{"id":"https://openalex.org/W4391697803","doi":"https://doi.org/10.1109/icsai61474.2023.10423325","title":"Dynamic Residual Illuminating Network for Low-Light Image Enhancement","display_name":"Dynamic Residual Illuminating Network for Low-Light Image Enhancement","publication_year":2023,"publication_date":"2023-12-16","ids":{"openalex":"https://openalex.org/W4391697803","doi":"https://doi.org/10.1109/icsai61474.2023.10423325"},"language":"en","primary_location":{"id":"doi:10.1109/icsai61474.2023.10423325","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsai61474.2023.10423325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 9th International Conference on Systems and Informatics (ICSAI)","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/A5101303214","display_name":"Xueyang Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xueyang Zhong","raw_affiliation_strings":["Wuhan Institute of Technology,School of Computer Science & Engineering,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology,School of Computer Science & Engineering,Wuhan,China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042308134","display_name":"Haihui Wang","orcid":"https://orcid.org/0000-0001-6345-0349"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihui Wang","raw_affiliation_strings":["Wuhan Institute of Technology,School of Computer Science & Engineering,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology,School of Computer Science & Engineering,Wuhan,China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034385024","display_name":"Yanpu Chen","orcid":"https://orcid.org/0000-0001-7355-3480"},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanpu Chen","raw_affiliation_strings":["Wuhan Institute of Technology,School of Computer Science & Engineering,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan Institute of Technology,School of Computer Science & Engineering,Wuhan,China","institution_ids":["https://openalex.org/I91125648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101303214"],"corresponding_institution_ids":["https://openalex.org/I91125648"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19978263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995999932289124,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994999766349792,"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/residual","display_name":"Residual","score":0.6364777684211731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5947503447532654},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5094335675239563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4834809899330139},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"Image enhancement","score":0.4827508330345154},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4187758266925812},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11293202638626099}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6364777684211731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5947503447532654},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5094335675239563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4834809899330139},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.4827508330345154},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4187758266925812},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11293202638626099}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsai61474.2023.10423325","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsai61474.2023.10423325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 9th International Conference on Systems and Informatics (ICSAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2058333183","https://openalex.org/W2076205488","https://openalex.org/W2254039850","https://openalex.org/W2515315308","https://openalex.org/W2783399029","https://openalex.org/W2948354154","https://openalex.org/W2949187370","https://openalex.org/W2952773607","https://openalex.org/W2955863859","https://openalex.org/W2964101377","https://openalex.org/W2981718299","https://openalex.org/W3035297694","https://openalex.org/W3035731588","https://openalex.org/W3042993386","https://openalex.org/W3108679343","https://openalex.org/W3121661546","https://openalex.org/W3186033197","https://openalex.org/W3199334903","https://openalex.org/W4308238078","https://openalex.org/W4313059954","https://openalex.org/W6754146604","https://openalex.org/W6755037456"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"A":[0],"low-light":[1,95],"image":[2,5],"is":[3,7,46,58],"an":[4,16],"that":[6,49],"taken":[8],"under":[9],"insufficient":[10],"lighting":[11],"conditions":[12],"or":[13],"captured":[14],"by":[15,60],"underexposed":[17],"camera.":[18],"Low-light":[19,43],"images":[20,56],"commonly":[21],"exhibit":[22],"characteristics":[23],"such":[24],"as":[25,122],"reduced":[26],"contrast,":[27],"diminished":[28],"brightness,":[29],"pronounced":[30],"noise,":[31],"and":[32,41,57,85,119,125,147,162],"color":[33],"distortion,":[34],"which":[35],"make":[36],"them":[37,121],"difficult":[38],"to":[39,83,127,140,144],"see":[40],"process.":[42],"Image":[44],"Enhancement":[45],"a":[47,103,141],"task":[48],"involves":[50],"improving":[51],"the":[52,107,114,123,153],"qualities":[53],"of":[54,155],"these":[55,99],"dominated":[59],"deep":[61,67],"learning":[62,68],"approaches":[63],"nowadays.":[64],"However,":[65],"most":[66],"methods":[69],"utilize":[70],"standard":[71],"convolution":[72],"with":[73],"fixed":[74],"kernels":[75],"in":[76,93,135,159],"their":[77],"CNN":[78],"architectures,":[79],"hindering":[80],"model\u2019s":[81],"capability":[82],"process":[84,128],"recover":[86],"more":[87,129],"information.":[88],"Besides,":[89],"noise":[90,146],"remains":[91],"challenging":[92],"recovering":[94],"images.":[96],"To":[97],"mitigate":[98],"issues,":[100],"we":[101,112,132],"propose":[102],"model":[104,158],"based":[105],"on":[106],"Deep":[108],"Lightening":[109],"Network":[110],"(DLN),":[111],"modify":[113,133],"Dynamic":[115],"Region-Aware":[116],"Convolution":[117],"(DRConv)":[118],"serve":[120],"encoder":[124],"decoder":[126],"intrinsic":[130],"features,":[131],"Residual":[134,136],"Dense":[137],"Block":[138],"(RRDB)":[139],"lighter":[142],"one":[143],"reduce":[145],"alleviate":[148],"computational":[149],"burden.":[150],"Experiments":[151],"demonstrate":[152],"advantages":[154],"our":[156],"proposed":[157],"quantitative":[160],"evaluation":[161],"visual":[163],"quality.":[164]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}