{"id":"https://openalex.org/W4253379369","doi":"https://doi.org/10.1109/mmsp53017.2021.9733476","title":"Hazing or Dehazing: the big dilemma for object detection","display_name":"Hazing or Dehazing: the big dilemma for object detection","publication_year":2021,"publication_date":"2021-10-06","ids":{"openalex":"https://openalex.org/W4253379369","doi":"https://doi.org/10.1109/mmsp53017.2021.9733476"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp53017.2021.9733476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp53017.2021.9733476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5058862347","display_name":"Simoni Panayi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162095","display_name":"Cytoskeleton (United States)","ror":"https://ror.org/05ent1n34","country_code":"US","type":"company","lineage":["https://openalex.org/I4210162095"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Simoni Panayi","raw_affiliation_strings":["CYENS Centre of Excellence,DeepCamera MRG Lab","DeepCamera MRG Lab, CYENS Centre of Excellence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CYENS Centre of Excellence,DeepCamera MRG Lab","institution_ids":["https://openalex.org/I4210162095"]},{"raw_affiliation_string":"DeepCamera MRG Lab, CYENS Centre of Excellence","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010329554","display_name":"Alessandro Artusi","orcid":"https://orcid.org/0000-0002-4502-663X"},"institutions":[{"id":"https://openalex.org/I4210162095","display_name":"Cytoskeleton (United States)","ror":"https://ror.org/05ent1n34","country_code":"US","type":"company","lineage":["https://openalex.org/I4210162095"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alessandro Artusi","raw_affiliation_strings":["CYENS Centre of Excellence,DeepCamera MRG Lab","DeepCamera MRG Lab, CYENS Centre of Excellence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CYENS Centre of Excellence,DeepCamera MRG Lab","institution_ids":["https://openalex.org/I4210162095"]},{"raw_affiliation_string":"DeepCamera MRG Lab, CYENS Centre of Excellence","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210162095"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.23899713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9984999895095825,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996399998664856,"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":0.8255935907363892},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6827610731124878},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6586587429046631},{"id":"https://openalex.org/keywords/haze","display_name":"Haze","score":0.6493549942970276},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6474617123603821},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6466197371482849},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6139990091323853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6022146344184875},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5882397294044495},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4942169487476349},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47618594765663147},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4643535912036896},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4146310091018677},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3125646710395813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8255935907363892},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6827610731124878},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6586587429046631},{"id":"https://openalex.org/C79974267","wikidata":"https://www.wikidata.org/wiki/Q643546","display_name":"Haze","level":2,"score":0.6493549942970276},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6474617123603821},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6466197371482849},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6139990091323853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6022146344184875},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5882397294044495},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4942169487476349},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47618594765663147},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4643535912036896},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4146310091018677},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3125646710395813},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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:10.1109/mmsp53017.2021.9733476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp53017.2021.9733476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.550000011920929,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W1990592195","https://openalex.org/W1995903777","https://openalex.org/W2025547231","https://openalex.org/W2028990532","https://openalex.org/W2029143333","https://openalex.org/W2065002911","https://openalex.org/W2114867966","https://openalex.org/W2139137304","https://openalex.org/W2147318913","https://openalex.org/W2156936307","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2256362396","https://openalex.org/W2262919957","https://openalex.org/W2518979500","https://openalex.org/W2519481857","https://openalex.org/W2557728737","https://openalex.org/W2748021867","https://openalex.org/W2754480022","https://openalex.org/W2779176852","https://openalex.org/W2791451704","https://openalex.org/W2792830341","https://openalex.org/W2894289548","https://openalex.org/W2895033814","https://openalex.org/W2896302292","https://openalex.org/W2941547246","https://openalex.org/W2955889502","https://openalex.org/W2963074253","https://openalex.org/W2963928582","https://openalex.org/W2964119864","https://openalex.org/W2968762770","https://openalex.org/W2976715267","https://openalex.org/W2997210448","https://openalex.org/W2998249728","https://openalex.org/W3011919688","https://openalex.org/W3013338555","https://openalex.org/W3034278302","https://openalex.org/W3034971973","https://openalex.org/W3106250896","https://openalex.org/W3109202794","https://openalex.org/W3110643118","https://openalex.org/W3112782334","https://openalex.org/W3121281282","https://openalex.org/W3165163215","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6647720530","https://openalex.org/W6744393451","https://openalex.org/W6747235268","https://openalex.org/W6785652829","https://openalex.org/W6787088174"],"related_works":["https://openalex.org/W2397673276","https://openalex.org/W2595172197","https://openalex.org/W2318437963","https://openalex.org/W2348696601","https://openalex.org/W2394444438","https://openalex.org/W2377355001","https://openalex.org/W2387386748","https://openalex.org/W2377493372","https://openalex.org/W2964624622","https://openalex.org/W4388446985"],"abstract_inverted_index":{"One":[0],"of":[1,19,29,32,67,77,121,144],"the":[2,6,16,20,59,65,91,104,119,128,142,145,151,178,183],"biggest":[3],"adversaries":[4],"to":[5,25,57,64,90,98,107,126,149,181],"computer":[7],"vision":[8,49,109],"pipeline":[9],"is":[10,96,162,174],"bad":[11],"weather":[12],"which":[13,55],"can":[14,35],"deteriorate":[15],"visual":[17,61],"quality":[18],"captured":[21],"images":[22],"and":[23,41,135,170],"lead":[24],"a":[26,116,163],"decreased":[27],"performance":[28],"tasks.":[30,110],"Examples":[31],"such":[33,71],"tasks":[34],"include":[36],"image":[37,79],"classification,":[38],"object":[39,122],"detection":[40,123,152,171],"semantic":[42],"segmentation.":[43],"To":[44,111],"ameliorate":[45],"this":[46,112,132],"acquisition":[47],"bottleneck,":[48],"experts":[50],"have":[51],"developed":[52],"restoration":[53],"approaches":[54,102],"aim":[56],"recover":[58],"lost":[60],"information":[62],"due":[63],"presence":[66],"poor":[68],"climactic":[69],"conditions":[70,169],"as":[72,138,140],"atmospheric":[73,136],"haze.":[74],"The":[75],"technique":[76],"single":[78],"dehazing":[80,147,179],"has":[81],"achieved":[82],"great":[83],"strides":[84],"in":[85],"producing":[86],"aesthetically":[87],"pleasing":[88],"restorations":[89],"human":[92],"perception.":[93],"However,":[94],"it":[95],"important":[97],"establish":[99],"whether":[100],"these":[101],"bring":[103],"same":[105],"merits":[106],"high-level":[108,133],"end,":[113],"we":[114,157],"formulate":[115],"study":[117],"around":[118],"task":[120,134],"that":[124,159],"aims":[125],"uncover":[127],"underlying":[129],"relationship":[130,166],"between":[131,167],"haze":[137],"well":[139],"examine":[141],"ability":[143],"current":[146],"process":[148,180],"enhance":[150],"performance.":[153],"From":[154],"our":[155],"experiments":[156],"find":[158],"while":[160],"there":[161,173],"clear":[164],"negative":[165],"hazy":[168],"performance,":[172],"little":[175],"help":[176],"from":[177],"achieve":[182],"desired":[184],"haze-free":[185],"results.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
