{"id":"https://openalex.org/W4383108568","doi":"https://doi.org/10.1109/icra48891.2023.10160477","title":"DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning Methods","display_name":"DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning Methods","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108568","doi":"https://doi.org/10.1109/icra48891.2023.10160477"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","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/A5026786490","display_name":"Stewart Jamieson","orcid":"https://orcid.org/0000-0003-4842-0373"},"institutions":[{"id":"https://openalex.org/I46020346","display_name":"American Institute of Aeronautics and Astronautics","ror":"https://ror.org/00a1rzv11","country_code":"US","type":"other","lineage":["https://openalex.org/I46020346"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Stewart Jamieson","raw_affiliation_strings":["MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering","Department of Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT)"],"affiliations":[{"raw_affiliation_string":"MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering","institution_ids":[]},{"raw_affiliation_string":"Department of Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT)","institution_ids":["https://openalex.org/I46020346","https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011665886","display_name":"Jonathan P. How","orcid":"https://orcid.org/0000-0001-8576-1930"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]},{"id":"https://openalex.org/I46020346","display_name":"American Institute of Aeronautics and Astronautics","ror":"https://ror.org/00a1rzv11","country_code":"US","type":"other","lineage":["https://openalex.org/I46020346"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan P. How","raw_affiliation_strings":["Massachusetts Institute of Technology (MIT),Department of Aeronautics and Astronautics","Department of Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT)"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology (MIT),Department of Aeronautics and Astronautics","institution_ids":["https://openalex.org/I46020346","https://openalex.org/I63966007"]},{"raw_affiliation_string":"Department of Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT)","institution_ids":["https://openalex.org/I46020346","https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072400128","display_name":"Yogesh Girdhar","orcid":"https://orcid.org/0000-0001-9510-9639"},"institutions":[{"id":"https://openalex.org/I66958751","display_name":"Woods Hole Oceanographic Institution","ror":"https://ror.org/03zbnzt98","country_code":"US","type":"funder","lineage":["https://openalex.org/I66958751"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yogesh Girdhar","raw_affiliation_strings":["Woods Hole Oceanographic Institution (WHOI),Applied Ocean Physics and Engineering Department","Applied Ocean Physics and Engineering Department, Woods Hole Oceanographic Institution (WHOI)"],"affiliations":[{"raw_affiliation_string":"Woods Hole Oceanographic Institution (WHOI),Applied Ocean Physics and Engineering Department","institution_ids":["https://openalex.org/I66958751"]},{"raw_affiliation_string":"Applied Ocean Physics and Engineering Department, Woods Hole Oceanographic Institution (WHOI)","institution_ids":["https://openalex.org/I66958751"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026786490"],"corresponding_institution_ids":["https://openalex.org/I46020346","https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":2.4563,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.909844,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3095","last_page":"3101"},"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":0.9937999844551086,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9936000108718872,"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/underwater","display_name":"Underwater","score":0.913388729095459},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7125629782676697},{"id":"https://openalex.org/keywords/color-correction","display_name":"Color correction","score":0.7069733738899231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6989938020706177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6713299751281738},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6700607538223267},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5606675148010254},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4390578866004944},{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.4218553304672241},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4200056791305542},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3631732165813446},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11075437068939209}],"concepts":[{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.913388729095459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125629782676697},{"id":"https://openalex.org/C2779495555","wikidata":"https://www.wikidata.org/wiki/Q5148596","display_name":"Color correction","level":3,"score":0.7069733738899231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6989938020706177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6713299751281738},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6700607538223267},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5606675148010254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4390578866004944},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.4218553304672241},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4200056791305542},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3631732165813446},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11075437068939209},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1950883283","https://openalex.org/W1973569872","https://openalex.org/W1975636777","https://openalex.org/W1976263166","https://openalex.org/W1986431218","https://openalex.org/W1992563911","https://openalex.org/W2052090926","https://openalex.org/W2094438760","https://openalex.org/W2128254161","https://openalex.org/W2148728346","https://openalex.org/W2168359206","https://openalex.org/W2413870294","https://openalex.org/W2567510167","https://openalex.org/W2593797484","https://openalex.org/W2798898057","https://openalex.org/W2919115771","https://openalex.org/W2950055287","https://openalex.org/W2960710867","https://openalex.org/W2963359064","https://openalex.org/W2964088115","https://openalex.org/W2991196524","https://openalex.org/W3009406242","https://openalex.org/W3010750023","https://openalex.org/W3082020764","https://openalex.org/W3091696636","https://openalex.org/W3099025816","https://openalex.org/W3099932909","https://openalex.org/W3100476583","https://openalex.org/W3109469519","https://openalex.org/W3117961507","https://openalex.org/W3120613243","https://openalex.org/W3153945974","https://openalex.org/W3170240973","https://openalex.org/W3203980564","https://openalex.org/W3211209457","https://openalex.org/W4285507493","https://openalex.org/W4295312788","https://openalex.org/W4297022287","https://openalex.org/W4310480301","https://openalex.org/W4312779355","https://openalex.org/W4322732128","https://openalex.org/W4383108665","https://openalex.org/W6755587996","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W4226332782","https://openalex.org/W4389777547","https://openalex.org/W4313029978","https://openalex.org/W2616936297","https://openalex.org/W4383108568","https://openalex.org/W4323651220","https://openalex.org/W4386797943","https://openalex.org/W3007932172","https://openalex.org/W2985484535","https://openalex.org/W3175729806"],"abstract_inverted_index":{"Successful":[0],"applications":[1],"of":[2,65,74,100,128],"complex":[3],"vision-based":[4,53,175],"behaviours":[5],"underwater":[6,32,42,59,77,94,120],"have":[7,82],"lagged":[8],"behind":[9],"progress":[10],"in":[11,31],"terrestrial":[12],"and":[13],"aerial":[14],"domains.":[15],"This":[16],"is":[17,87],"largely":[18],"due":[19],"to":[20,51,69,76,142,151,157,171],"the":[21,27,63,71,125,143],"degraded":[22],"image":[23,33,66,121],"quality":[24],"resulting":[25],"from":[26,41],"physical":[28],"phenomena":[29],"involved":[30],"formation.":[34],"Spectrally-selective":[35],"light":[36],"attenuation":[37],"drains":[38],"some":[39],"colors":[40],"images":[43,154],"while":[44,148],"backscattering":[45],"adds":[46],"others,":[47],"making":[48,160],"it":[49,161],"challenging":[50],"perform":[52],"tasks":[54],"underwater.":[55],"State-of-the-art":[56],"methods":[57,81],"for":[58,89,105,163],"color":[60,75,107],"correction":[61],"optimize":[62],"parameters":[64],"formation":[67,122],"models":[68],"restore":[70],"full":[72],"spectrum":[73],"imagery.":[78],"However,":[79],"these":[80],"high":[83],"computational":[84,126],"complexity":[85],"that":[86,116,137],"unfavourable":[88],"realtime":[90],"use":[91,164],"by":[92],"autonomous":[93],"vehicles":[95],"(AUVs),":[96],"as":[97,167],"a":[98,113,118,168],"result":[99],"having":[101],"been":[102],"primarily":[103],"designed":[104],"offline":[106],"correction.":[108],"Here,":[109],"we":[110,135],"present":[111],"DeepSeeColor,":[112],"novel":[114],"algorithm":[115,146],"combines":[117],"state-of-the-art":[119],"model":[123],"with":[124],"efficiency":[127],"deep":[129],"learning":[130],"frameworks.":[131],"In":[132],"our":[133],"experiments,":[134],"show":[136],"DeepSeeColor":[138],"offers":[139],"comparable":[140],"performance":[141],"popular":[144],"\u201cSea-Thru\u201d":[145],"[1]":[147],"being":[149],"able":[150],"rapidly":[152],"process":[153],"at":[155],"up":[156],"60Hz,":[158],"thus":[159],"suitable":[162],"onboard":[165],"AUVs":[166],"preprocessing":[169],"step":[170],"enable":[172],"more":[173],"robust":[174],"behaviours.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}