{"id":"https://openalex.org/W3201662659","doi":"https://doi.org/10.1145/3458380.3458387","title":"Deep Learning-Enabled Low-light Image Enhancement In Maritime Video Surveillance","display_name":"Deep Learning-Enabled Low-light Image Enhancement In Maritime Video Surveillance","publication_year":2021,"publication_date":"2021-02-26","ids":{"openalex":"https://openalex.org/W3201662659","doi":"https://doi.org/10.1145/3458380.3458387","mag":"3201662659"},"language":"en","primary_location":{"id":"doi:10.1145/3458380.3458387","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3458380.3458387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Digital Signal Processing","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/A5078860408","display_name":"Wenbo Yang","orcid":"https://orcid.org/0000-0001-7184-2481"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenbo Yang","raw_affiliation_strings":["Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077457192","display_name":"Zhouheng Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhouheng Ge","raw_affiliation_strings":["Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061907283","display_name":"Ryan Wen Liu","orcid":"https://orcid.org/0000-0002-1591-5583"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ryan Wen Liu","raw_affiliation_strings":["Wuhan University of Technology and Wuhan University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology and Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078860408"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.11921569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"40","last_page":"45"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9976000189781189,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.7195523977279663},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6074430346488953},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.6020124554634094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5944597721099854},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.5831124782562256},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5215463638305664},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.474275678396225},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3416104018688202},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12463772296905518},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08855479955673218}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7195523977279663},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6074430346488953},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.6020124554634094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5944597721099854},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.5831124782562256},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5215463638305664},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.474275678396225},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3416104018688202},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12463772296905518},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08855479955673218},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3458380.3458387","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3458380.3458387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Digital Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1621368367","https://openalex.org/W1932188298","https://openalex.org/W1986086122","https://openalex.org/W2038713671","https://openalex.org/W2057995993","https://openalex.org/W2074227110","https://openalex.org/W2116899452","https://openalex.org/W2116973876","https://openalex.org/W2118330267","https://openalex.org/W2121900453","https://openalex.org/W2150721269","https://openalex.org/W2254039850","https://openalex.org/W2508457857","https://openalex.org/W2566376500","https://openalex.org/W2963446712","https://openalex.org/W2963840672","https://openalex.org/W2999653953","https://openalex.org/W6725739302"],"related_works":["https://openalex.org/W2387055199","https://openalex.org/W2313061941","https://openalex.org/W2588661485","https://openalex.org/W1953485902","https://openalex.org/W2560215812","https://openalex.org/W1501776718","https://openalex.org/W2052546562","https://openalex.org/W3175896399","https://openalex.org/W2605640648","https://openalex.org/W2615136228"],"abstract_inverted_index":{"With":[0],"the":[1,12,20,26,42,57,68,71,76,109,114,130,157,166,179,184,195,203,208,212,220,224,238],"rapid":[2],"development":[3],"of":[4,29,44,61,70,75,133,168,186,211,223,233],"artificial":[5],"intelligence":[6],"technology":[7],"and":[8,49,59,103,118,128,147,155,160,170,205,217],"computer":[9],"vision":[10],"technology,":[11],"maritime":[13],"camera":[14],"is":[15,124,176],"gradually":[16],"applied":[17,106],"to":[18,107,113,126,137,164,182,241],"monitoring":[19,27,209,221],"inland":[21,30,62,213,225],"river":[22,31,63,214,226],"bridge":[23,32,215,239],"area.":[24],"However,":[25],"images":[28,188,210],"area":[33,216,240],"obtained":[34],"under":[35],"low":[36,45,47,50,77,84,110],"light":[37,78,85,111,116],"imaging":[38,73],"conditions":[39],"usually":[40],"have":[41],"characteristics":[43],"brightness,":[46],"contrast,":[48],"resolution,":[51],"which":[52],"brings":[53],"many":[54],"restrictions":[55],"on":[56,90],"supervision":[58],"management":[60],"traffic.":[64],"To":[65],"further":[66,218],"solve":[67],"problem":[69],"poor":[72],"effect":[74,222],"images,":[79],"this":[80,200],"paper":[81,201],"proposes":[82],"a":[83,139,231,242],"image":[86,112,142],"enhancement":[87],"method":[88],"based":[89],"deep":[91],"learning.":[92],"Four":[93],"typical":[94],"neural":[95],"network":[96,197],"structures":[97],"(i.e.,":[98],"Attention-guided":[99],"CNN,":[100],"DnCNN,":[101],"DenseNet,":[102],"Noise2Noise)":[104],"are":[105],"mapping":[108],"positive":[115],"image,":[117],"then":[119],"an":[120],"EN-Net":[121,149],"(Enhancement":[122],"Network)":[123],"used":[125,177],"balance":[127],"enhance":[129],"output":[131,141],"results":[132,192],"these":[134],"four":[135],"networks,":[136],"get":[138],"final":[140],"that":[143,194],"has":[144],"been":[145],"splined":[146],"enhanced.":[148],"will":[150],"adopt":[151],"U-Net's":[152],"basic":[153],"structure":[154],"integrate":[156],"local":[158],"residual":[159,162],"global":[161],"modules":[163],"increase":[165],"diversity":[167],"features":[169],"speed":[171],"up":[172],"training.":[173],"L1":[174],"norm":[175],"as":[178],"loss":[180],"function":[181],"improve":[183],"quality":[185],"enhanced":[187],"further.":[189],"The":[190],"experimental":[191],"show":[193],"depth":[196],"proposed":[198],"in":[199,237],"improves":[202,219],"brightness":[204],"contrast":[206],"with":[207],"bridges":[227],"area,":[228],"thus":[229],"providing":[230],"guarantee":[232],"water":[234],"traffic":[235],"safety":[236],"certain":[243],"extent.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
