{"id":"https://openalex.org/W4408241899","doi":"https://doi.org/10.1109/cisp-bmei64163.2024.10906253","title":"AE-YOLO: Asymptotic Enhancement for Low-Light Object Detection","display_name":"AE-YOLO: Asymptotic Enhancement for Low-Light Object Detection","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4408241899","doi":"https://doi.org/10.1109/cisp-bmei64163.2024.10906253"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei64163.2024.10906253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei64163.2024.10906253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5085201998","display_name":"Rui Wu","orcid":"https://orcid.org/0000-0001-7133-185X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Wu","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101399361","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0002-4817-8858"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Huang","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052843284","display_name":"Xinrui Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinrui Xu","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085201998"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.7895,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75189955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"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":0.9757999777793884,"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":0.9757999777793884,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9254999756813049,"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/object-detection","display_name":"Object detection","score":0.6381171941757202},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5926083326339722},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5530611872673035},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4743187129497528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4394809305667877},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.19264286756515503}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6381171941757202},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5926083326339722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5530611872673035},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4743187129497528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4394809305667877},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.19264286756515503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei64163.2024.10906253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei64163.2024.10906253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2102605133","https://openalex.org/W2193145675","https://openalex.org/W2963766909","https://openalex.org/W3035731588","https://openalex.org/W3121661546","https://openalex.org/W3174792937","https://openalex.org/W3204374989","https://openalex.org/W4226042837","https://openalex.org/W4361829719","https://openalex.org/W4384525598","https://openalex.org/W4385245566","https://openalex.org/W4386066362","https://openalex.org/W4386939303","https://openalex.org/W4390872514","https://openalex.org/W4390872559","https://openalex.org/W4402754076","https://openalex.org/W6750227808","https://openalex.org/W6764322716","https://openalex.org/W6809646742","https://openalex.org/W6845221098","https://openalex.org/W6862285343"],"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":{"Object":[0],"detection":[1,17,45,63,79,167],"has":[2],"achieved":[3],"significant":[4],"advancements":[5],"due":[6],"to":[7,40,72,77,116],"the":[8,55,58,82,99,133,138,153],"continuous":[9],"development":[10],"of":[11,57,135,155],"deep":[12],"learning":[13],"technology;":[14],"however,":[15],"object":[16,44,147,166],"in":[18,120,160],"low-light":[19,146,170],"conditions":[20],"remains":[21],"a":[22,42,113,124],"challenge.":[23],"To":[24,53],"address":[25],"this":[26],"issue,":[27],"we":[28],"propose":[29],"an":[30,75,88],"asymptotic":[31],"enhancement":[32,59,68,71,84,110],"network":[33,60,85,111],"(AENet)":[34],"and":[35,69,97,164],"integrate":[36],"it":[37],"with":[38],"YOLOv3":[39],"develop":[41],"novel":[43],"framework":[46,159],"called":[47],"AE-YOLO,":[48],"specially":[49],"designed":[50,144],"for":[51,61,105,127,145],"low-light.":[52],"maximize":[54],"benefits":[56],"downstream":[62],"tasks,":[64],"AENet":[65],"employs":[66],"pixel-level":[67,83],"feature-level":[70,109],"adaptively":[73],"enhance":[74],"image":[76,89,162],"improve":[78],"performance.":[80],"Specifically,":[81],"first":[86],"divides":[87],"into":[90],"<tex":[91],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[92],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$8":[93],"\\times":[94],"8$</tex>":[95],"patches,":[96],"applies":[98],"Yeo-Johnson":[100],"transform":[101],"on":[102],"each":[103],"patch":[104],"dynamic":[106],"enhancement.":[107,130],"The":[108,149],"utilizes":[112],"prompt":[114],"block":[115],"recover":[117],"details":[118],"lost":[119],"dark,":[121],"followed":[122],"by":[123],"transformer":[125],"layer":[126],"further":[128],"feature":[129],"We":[131],"evaluated":[132],"performance":[134],"AE-YOLO":[136,158],"using":[137],"ExDark":[139],"dataset,":[140],"which":[141],"is":[142],"specifically":[143],"detection.":[148],"experimental":[150],"results":[151],"demonstrate":[152],"effectiveness":[154],"our":[156],"proposed":[157],"enhancing":[161],"quality":[163],"improving":[165],"accuracy":[168],"under":[169],"conditions.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
