{"id":"https://openalex.org/W7131663833","doi":"https://doi.org/10.1007/s11042-026-21439-8","title":"Beyond labels: Semi-supervised underwater habitat detection with image enhancement as augmentation","display_name":"Beyond labels: Semi-supervised underwater habitat detection with image enhancement as augmentation","publication_year":2026,"publication_date":"2026-02-26","ids":{"openalex":"https://openalex.org/W7131663833","doi":"https://doi.org/10.1007/s11042-026-21439-8"},"language":"en","primary_location":{"id":"doi:10.1007/s11042-026-21439-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-026-21439-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11042-026-21439-8.pdf","source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11042-026-21439-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050245118","display_name":"Rim Rahali","orcid":"https://orcid.org/0000-0002-5908-3002"},"institutions":[{"id":"https://openalex.org/I12449238","display_name":"Universit\u00e9 d'Orl\u00e9ans","ror":"https://ror.org/014zrew76","country_code":"FR","type":"education","lineage":["https://openalex.org/I12449238"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Rim Rahali","raw_affiliation_strings":["University of Orleans, LIFO UR 4022, INSA-CVL, Orleans, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Orleans, LIFO UR 4022, INSA-CVL, Orleans, France","institution_ids":["https://openalex.org/I12449238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101471226","display_name":"Nhu-Van Nguyen","orcid":"https://orcid.org/0000-0003-2271-6918"},"institutions":[{"id":"https://openalex.org/I12449238","display_name":"Universit\u00e9 d'Orl\u00e9ans","ror":"https://ror.org/014zrew76","country_code":"FR","type":"education","lineage":["https://openalex.org/I12449238"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Vincent Nguyen","raw_affiliation_strings":["University of Orleans, LIFO UR 4022, INSA-CVL, Orleans, France"],"raw_orcid":"https://orcid.org/0000-0003-2271-6918","affiliations":[{"raw_affiliation_string":"University of Orleans, LIFO UR 4022, INSA-CVL, Orleans, France","institution_ids":["https://openalex.org/I12449238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101471226"],"corresponding_institution_ids":["https://openalex.org/I12449238"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38080078,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"85","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.579200029373169,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.579200029373169,"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/T11019","display_name":"Image Enhancement Techniques","score":0.1340000033378601,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.0421999990940094,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.8016999959945679},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5509999990463257},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5480999946594238},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5418000221252441},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4307999908924103},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41659998893737793},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3910999894142151}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8671000003814697},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.8016999959945679},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5509999990463257},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5480999946594238},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5418000221252441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5393999814987183},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41659998893737793},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3910999894142151},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34940001368522644},{"id":"https://openalex.org/C185933670","wikidata":"https://www.wikidata.org/wiki/Q52105","display_name":"Habitat","level":2,"score":0.3463999927043915},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3375999927520752},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C134037308","wikidata":"https://www.wikidata.org/wiki/Q6764288","display_name":"Marine habitats","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11042-026-21439-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-026-21439-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11042-026-21439-8.pdf","source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11042-026-21439-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-026-21439-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11042-026-21439-8.pdf","source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8496213555335999,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G8668791235","display_name":"Weakly supervised learning and efficient deep models deployed on an ROV for the detection and the classification of underwater objects","funder_award_id":"ANR-21-ASRO-0003","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7131663833.pdf","grobid_xml":"https://content.openalex.org/works/W7131663833.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1966005655","https://openalex.org/W1981147639","https://openalex.org/W2081140338","https://openalex.org/W2194775991","https://openalex.org/W2256362396","https://openalex.org/W2588644812","https://openalex.org/W2759875922","https://openalex.org/W2763503841","https://openalex.org/W2772435728","https://openalex.org/W2949736877","https://openalex.org/W2980651313","https://openalex.org/W2999811308","https://openalex.org/W3006777311","https://openalex.org/W3012573144","https://openalex.org/W3028220388","https://openalex.org/W3035524453","https://openalex.org/W3047626901","https://openalex.org/W3081847025","https://openalex.org/W3090063164","https://openalex.org/W3108328895","https://openalex.org/W3129419153","https://openalex.org/W3135937998","https://openalex.org/W3145601439","https://openalex.org/W3162410350","https://openalex.org/W3172507542","https://openalex.org/W3179069071","https://openalex.org/W3180668190","https://openalex.org/W3185219364","https://openalex.org/W4210805297","https://openalex.org/W4226333856","https://openalex.org/W4285821234","https://openalex.org/W4296282860","https://openalex.org/W4313030842","https://openalex.org/W4315498985","https://openalex.org/W4319982106","https://openalex.org/W4320033720","https://openalex.org/W4322732128","https://openalex.org/W4377079715","https://openalex.org/W4380318746","https://openalex.org/W4384938677","https://openalex.org/W4386267462","https://openalex.org/W4386595026","https://openalex.org/W4390493314","https://openalex.org/W4399384347","https://openalex.org/W4399517126","https://openalex.org/W4402742664","https://openalex.org/W4405868631","https://openalex.org/W4408111608","https://openalex.org/W4412722892"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"progress":[1],"in":[2,45,89,151],"deep":[3],"learning":[4,66],"for":[5,68,79],"object":[6],"detection":[7],"has":[8],"largely":[9],"relied":[10],"on":[11],"big,":[12],"well-labeled":[13],"datasets.":[14,104],"But":[15],"when":[16],"it":[17],"comes":[18],"to":[19],"underwater":[20,130],"imagery,":[21],"annotation":[22],"becomes":[23],"a":[24,33,39,141],"real":[25],"challenge.":[26],"It":[27],"typically":[28],"requires":[29],"domain":[30],"experts":[31],"and":[32,102,126,144],"lot":[34],"of":[35,64,75,82,117,123,129,148],"manual":[36],"effort.":[37],"As":[38],"result,":[40],"building":[41],"large-scale":[42],"labeled":[43,83,118],"datasets":[44],"this":[46,57,138],"field":[47],"is":[48],"not":[49],"only":[50],"time-consuming":[51],"but":[52],"also":[53],"often":[54],"impractical.":[55],"In":[56],"paper,":[58],"we":[59,108],"present":[60],"an":[61,134],"in-depth":[62],"investigation":[63],"semi-supervised":[65],"models":[67,98],"marine":[69,152],"habitat":[70,153],"detection,":[71],"with":[72],"the":[73,77,90,100,115,121,127,146],"goal":[74],"reducing":[76],"need":[78],"large":[80],"amounts":[81],"data":[84],"while":[85],"maintaining":[86],"strong":[87],"performance":[88],"complex":[91],"conditions":[92],"found":[93],"underwater.":[94],"We":[95],"evaluate":[96],"these":[97,149],"using":[99],"Deepfish":[101],"UTDAC2020":[103],"By":[105],"extensive":[106],"experimentation,":[107],"explore":[109],"how":[110],"various":[111],"factors":[112],"influence":[113],"performance:":[114],"amount":[116],"training":[119],"data,":[120],"role":[122],"contrastive":[124],"learning,":[125],"application":[128],"image":[131],"enhancement":[132],"as":[133],"augmentation":[135],"technique.":[136],"Overall,":[137],"work":[139],"provides":[140],"detailed":[142],"analysis":[143],"highlights":[145],"potential":[147],"techniques":[150],"detection.":[154]},"counts_by_year":[],"updated_date":"2026-03-12T06:13:28.667946","created_date":"2026-02-27T00:00:00"}