{"id":"https://openalex.org/W4283459286","doi":"https://doi.org/10.1145/3533050.3533064","title":"A Novel Approach to Low Light Object Detection Using Exclusively Dark Images","display_name":"A Novel Approach to Low Light Object Detection Using Exclusively Dark Images","publication_year":2022,"publication_date":"2022-04-09","ids":{"openalex":"https://openalex.org/W4283459286","doi":"https://doi.org/10.1145/3533050.3533064"},"language":"en","primary_location":{"id":"doi:10.1145/3533050.3533064","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3533050.3533064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 6th International Conference on Intelligent Systems, Metaheuristics &amp; Swarm Intelligence","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/A5100462936","display_name":"Ankit Kumar","orcid":"https://orcid.org/0000-0001-9587-2861"},"institutions":[{"id":"https://openalex.org/I4210092007","display_name":"HLL Lifecare (India)","ror":"https://ror.org/00fz6qg20","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210092007"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankit Kumar","raw_affiliation_strings":["Softvan Pvt Ltd, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Softvan Pvt Ltd, India","institution_ids":["https://openalex.org/I4210092007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014562528","display_name":"Bijal Talati","orcid":"https://orcid.org/0000-0002-6683-1347"},"institutions":[{"id":"https://openalex.org/I4210093800","display_name":"Voluntary Health Association Of India","ror":"https://ror.org/00nezvm77","country_code":"IN","type":"nonprofit","lineage":["https://openalex.org/I4210093800"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bijal Talati","raw_affiliation_strings":["S.V.I.T, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"S.V.I.T, India","institution_ids":["https://openalex.org/I4210093800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049328262","display_name":"Mihir Rajput","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092007","display_name":"HLL Lifecare (India)","ror":"https://ror.org/00fz6qg20","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210092007"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mihir Rajput","raw_affiliation_strings":["Softvan Pvt Limited, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Softvan Pvt Limited, India","institution_ids":["https://openalex.org/I4210092007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019915904","display_name":"Harshal Trivedi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092007","display_name":"HLL Lifecare (India)","ror":"https://ror.org/00fz6qg20","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210092007"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harshal Trivedi","raw_affiliation_strings":["Softvan Pvt Limited, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Softvan Pvt Limited, India","institution_ids":["https://openalex.org/I4210092007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05024878,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"86","last_page":"92"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","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"}},"topics":[{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.998199999332428,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7786210179328918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7555781602859497},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6922885775566101},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.673730194568634},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6185430288314819},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5672760605812073},{"id":"https://openalex.org/keywords/light-intensity","display_name":"Light intensity","score":0.5461446642875671},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5392784476280212},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5175346732139587},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4893011748790741},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.48506394028663635},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.4677242040634155},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4408540725708008},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4284197688102722},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11855709552764893},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08405059576034546}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7786210179328918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7555781602859497},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6922885775566101},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.673730194568634},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6185430288314819},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5672760605812073},{"id":"https://openalex.org/C3020368824","wikidata":"https://www.wikidata.org/wiki/Q6546192","display_name":"Light intensity","level":2,"score":0.5461446642875671},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5392784476280212},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5175346732139587},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4893011748790741},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.48506394028663635},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.4677242040634155},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4408540725708008},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4284197688102722},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11855709552764893},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08405059576034546},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3533050.3533064","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3533050.3533064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 6th International Conference on Intelligent Systems, Metaheuristics &amp; Swarm Intelligence","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":21,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W1960182310","https://openalex.org/W1977792424","https://openalex.org/W2108598243","https://openalex.org/W2585123518","https://openalex.org/W2607037079","https://openalex.org/W2789876780","https://openalex.org/W2798843784","https://openalex.org/W2799265886","https://openalex.org/W2895236117","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963404857","https://openalex.org/W2963766909","https://openalex.org/W3005026984","https://openalex.org/W3013467123","https://openalex.org/W3042011474","https://openalex.org/W3147926912","https://openalex.org/W3157990341","https://openalex.org/W4213113494"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2011676020","https://openalex.org/W4387272257"],"abstract_inverted_index":{"The":[0,184],"efficiency":[1,26],"of":[2,16,27,38,50,61,87,119,139,148,186,196],"our":[3,19,158],"vision":[4,28],"highly":[5],"depends":[6],"on":[7,72],"the":[8,14,25,30,59,73,90,106,124,130,137,146,153,164,175,177,193,200],"light\u2019s":[9],"intensity.":[10],"In":[11],"dark":[12,92,107],"images,":[13],"intensity":[15,60],"light":[17,62,112],"in":[18,105,136,199],"surroundings":[20],"is":[21,41,64,143,172,189],"generally":[22],"lower,":[23],"reducing":[24],"and":[29,45,115,121,160],"capability":[31],"to":[32,55,126,190],"distinguish":[33],"different":[34,82,85,117],"objects.":[35],"An":[36],"analysis":[37],"lowlight":[39],"images":[40],"possible":[42],"with":[43,174],"handcrafted":[44],"learned":[46],"features.":[47],"This":[48,151],"process":[49],"object":[51,103],"recognition":[52,104,194],"also":[53,161],"needs":[54],"take":[56],"into":[57],"consideration":[58],"that":[63,108,163],"produced":[65],"by":[66,157],"a":[67,78,99],"particular":[68,79],"pixel":[69],"varies":[70],"depending":[71],"color":[74],"space":[75],"used":[76,96,128],"for":[77,102,133,145,181],"image":[80],"since":[81],"colors":[83],"produce":[84],"intensities":[86],"light.":[88,141],"Therefore,":[89],"exclusively":[91],"dataset":[93,101],"has":[94,123],"been":[95],"recently":[97],"as":[98,129],"benchmark":[100],"contains":[109],"10":[110],"low":[111,140],"illumination":[113],"types":[114],"12":[116],"categories":[118],"objects,":[120],"it":[122,171],"potential":[125,180],"be":[127],"standard":[131],"database":[132],"benchmarking":[134],"research":[135],"domain":[138],"CSPNet":[142],"essential":[144],"purpose":[147],"feature":[149],"extraction.":[150],"reduces":[152],"computational":[154],"load":[155],"required":[156],"model":[159],"ensures":[162],"accuracy":[165],"does":[166],"not":[167],"significantly":[168],"reduce.":[169],"When":[170],"coupled":[173],"CNN,":[176],"results":[178],"show":[179],"practical":[182],"applications.":[183],"goal":[185],"this":[187],"paper":[188],"further":[191],"improve":[192],"rate":[195],"various":[197],"objects":[198],"dark.":[201]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
