{"id":"https://openalex.org/W7203606946","doi":"https://doi.org/10.3390/jmse14161523","title":"HiFi-Det: Collaborative Multi-Scale Frequency-Domain Feature Optimization for Crown-of-Thorns Starfish Detection in Complex Underwater Environments","display_name":"HiFi-Det: Collaborative Multi-Scale Frequency-Domain Feature Optimization for Crown-of-Thorns Starfish Detection in Complex Underwater Environments","publication_year":2026,"publication_date":"2026-08-17","ids":{"openalex":"https://openalex.org/W7203606946","doi":"https://doi.org/10.3390/jmse14161523"},"language":"en","primary_location":{"id":"doi:10.3390/jmse14161523","doi":"https://doi.org/10.3390/jmse14161523","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jmse14161523","pdf_url":null,"source":{"id":"https://openalex.org/S2736865057","display_name":"Journal of Marine Science and Engineering","issn_l":"2077-1312","issn":["2077-1312"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Marine Science and Engineering","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/jmse14161523","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5147368696","display_name":"Sirong Qian","orcid":"https://orcid.org/0009-0009-2574-1108","observed_orcids":["https://orcid.org/0009-0009-2574-1108"]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sirong Qian","raw_affiliation_strings":["School of Computer Science and Engineering, Guangzhou Higher Education Mega Center, Sun Yat-sen University, No. 132 Waihuandong Road, Guangzhou 510006, China"],"raw_orcid":"https://orcid.org/0009-0009-2574-1108","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Guangzhou Higher Education Mega Center, Sun Yat-sen University, No. 132 Waihuandong Road, Guangzhou 510006, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5145152425","display_name":"Yuewen Huang","orcid":"https://orcid.org/0009-0005-1255-3993","observed_orcids":["https://orcid.org/0009-0005-1255-3993"]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuewen Huang","raw_affiliation_strings":["School of Computer Science and Engineering, Guangzhou Higher Education Mega Center, Sun Yat-sen University, No. 132 Waihuandong Road, Guangzhou 510006, China"],"raw_orcid":"https://orcid.org/0009-0005-1255-3993","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Guangzhou Higher Education Mega Center, Sun Yat-sen University, No. 132 Waihuandong Road, Guangzhou 510006, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100377186","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-7096-3633","observed_orcids":["https://orcid.org/0000-0002-7096-3633"]},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Wang","raw_affiliation_strings":["National Field Observation and Research Station (Hainan Nansha) for Coral Reef Ecosystem, Guangzhou 510300, China","South China Sea Ecological Center, Ministry of Natural Resources, Guangzhou 510300, China"],"raw_orcid":"https://orcid.org/0000-0002-7096-3633","affiliations":[{"raw_affiliation_string":"National Field Observation and Research Station (Hainan Nansha) for Coral Reef Ecosystem, Guangzhou 510300, China","institution_ids":[]},{"raw_affiliation_string":"South China Sea Ecological Center, Ministry of Natural Resources, Guangzhou 510300, China","institution_ids":["https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102205389","display_name":"Houlei Jia","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houlei Jia","raw_affiliation_strings":["National Field Observation and Research Station (Hainan Nansha) for Coral Reef Ecosystem, Guangzhou 510300, China","South China Sea Ecological Center, Ministry of Natural Resources, Guangzhou 510300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Field Observation and Research Station (Hainan Nansha) for Coral Reef Ecosystem, Guangzhou 510300, China","institution_ids":[]},{"raw_affiliation_string":"South China Sea Ecological Center, Ministry of Natural Resources, Guangzhou 510300, China","institution_ids":["https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045778370","display_name":"Xiaoyong Mei","orcid":"https://orcid.org/0000-0001-6422-1724","observed_orcids":["https://orcid.org/0000-0001-6422-1724"]},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyong Mei","raw_affiliation_strings":["Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua 321017, China"],"raw_orcid":"https://orcid.org/0000-0001-6422-1724","affiliations":[{"raw_affiliation_string":"Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua 321017, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024126710","display_name":"Fudan Zheng","orcid":"https://orcid.org/0000-0002-9664-012X","observed_orcids":["https://orcid.org/0000-0002-9664-012X"]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4405256355","display_name":"National Supercomputer Center in Guangzhou","ror":"https://ror.org/042999n30","country_code":"CN","type":"facility","lineage":["https://openalex.org/I157773358","https://openalex.org/I4405256355"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fudan Zheng","raw_affiliation_strings":["National SuperComputer Center in Guangzhou, Guangzhou Higher Education Mega Center, No. 132 Waihuandong Road, Guangzhou 510006, China","School of Computer Science and Engineering, Guangzhou Higher Education Mega Center, Sun Yat-sen University, No. 132 Waihuandong Road, Guangzhou 510006, China"],"raw_orcid":"https://orcid.org/0000-0002-9664-012X","affiliations":[{"raw_affiliation_string":"National SuperComputer Center in Guangzhou, Guangzhou Higher Education Mega Center, No. 132 Waihuandong Road, Guangzhou 510006, China","institution_ids":["https://openalex.org/I4405256355"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Guangzhou Higher Education Mega Center, Sun Yat-sen University, No. 132 Waihuandong Road, Guangzhou 510006, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024126710"],"corresponding_institution_ids":["https://openalex.org/I157773358","https://openalex.org/I4405256355"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":2.8589,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.93346702,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":"14","issue":"16","first_page":"1523","last_page":"1523"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8960000276565552,"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":0.8960000276565552,"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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.0625,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10341","display_name":"Coral and Marine Ecosystems Studies","score":0.00860000029206276,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/acanthaster-planci","display_name":"crown-of-thorns starfish","score":0.9409999847412109},{"id":"https://openalex.org/keywords/acanthaster","display_name":"Acanthaster","score":0.9549999833106995},{"id":"https://openalex.org/keywords/underwater-object-detection","display_name":"underwater object detection","score":0.7089999914169312},{"id":"https://openalex.org/keywords/coral-reef-monitoring","display_name":"coral reef monitoring","score":0.8550000190734863},{"id":"https://openalex.org/keywords/yolo11","display_name":"YOLOv11","score":0.8220000267028809},{"id":"https://openalex.org/keywords/wavelet-transform-convolution","display_name":"wavelet transform convolution","score":0.9639999866485596},{"id":"https://openalex.org/keywords/wiouv3-loss","display_name":"WIoUv3 loss","score":0.8429999947547913},{"id":"https://openalex.org/keywords/small-object-detection","display_name":"small object detection","score":0.7279999852180481},{"id":"https://openalex.org/keywords/coral-cover-loss","display_name":"coral cover decline","score":0.6129999756813049},{"id":"https://openalex.org/keywords/great-barrier-reef","display_name":"Great Barrier Reef","score":0.7129999995231628}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6427000164985657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5435000061988831},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.5217999815940857},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37369999289512634},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C58861099","wikidata":"https://www.wikidata.org/wiki/Q548838","display_name":"Handshaking","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34119999408721924},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3043000102043152},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29760000109672546},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2621999979019165},{"id":"https://openalex.org/C2779741766","wikidata":"https://www.wikidata.org/wiki/Q744513","display_name":"Acanthaster","level":4,"score":0.2615000009536743},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/jmse14161523","doi":"https://doi.org/10.3390/jmse14161523","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jmse14161523","pdf_url":null,"source":{"id":"https://openalex.org/S2736865057","display_name":"Journal of Marine Science and Engineering","issn_l":"2077-1312","issn":["2077-1312"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Marine Science and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0a4b27c087ae4001a26522630e107754","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/0a4b27c087ae4001a26522630e107754","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Marine Science and Engineering, Vol 14, Iss 16, p 1523 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/jmse14161523","doi":"https://doi.org/10.3390/jmse14161523","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jmse14161523","pdf_url":null,"source":{"id":"https://openalex.org/S2736865057","display_name":"Journal of Marine Science and Engineering","issn_l":"2077-1312","issn":["2077-1312"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Marine Science and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","display_name":"Life below water","score":1.0}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5756486058235168}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320316090","display_name":"Ministry of Natural Resources of the People's Republic of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W204065161","https://openalex.org/W585604970","https://openalex.org/W639708223","https://openalex.org/W1992396639","https://openalex.org/W2069864946","https://openalex.org/W2565639579","https://openalex.org/W2740394441","https://openalex.org/W2950628590","https://openalex.org/W2962858109","https://openalex.org/W2963857746","https://openalex.org/W3106850582","https://openalex.org/W4281554778","https://openalex.org/W4306253042","https://openalex.org/W4361793966","https://openalex.org/W4403887646","https://openalex.org/W4405269923","https://openalex.org/W4415101868","https://openalex.org/W4416626227","https://openalex.org/W4416964579","https://openalex.org/W7116930968"],"related_works":["https://openalex.org/W7065006813","https://openalex.org/W4414099809","https://openalex.org/W7125910473","https://openalex.org/W4416923075","https://openalex.org/W4405754474","https://openalex.org/W7043867833","https://openalex.org/W4416626227","https://openalex.org/W4415592879","https://openalex.org/W4399976742","https://openalex.org/W3217062691"],"abstract_inverted_index":{"Outbreaks":[0],"of":[1,13,116,178,258,335],"the":[2,92,114,163,172,206,220,230,237,244,256,259,262,283,306,333],"Crown-of-Thorns":[3],"Starfish":[4],"(COTS,":[5],"Acanthaster":[6],"spp.)":[7],"are":[8,30,58,247],"a":[9,103,111,131,146,187,287,309,314],"leading":[10],"biological":[11],"driver":[12],"coral":[14,79,184],"cover":[15],"loss,":[16],"making":[17,67],"timely":[18],"and":[19,32,62,77,84,165,186,216,225,272,302,324],"accurate":[20],"population":[21],"monitoring":[22,96],"essential":[23],"for":[24,154],"reef":[25],"management.":[26],"Conventional":[27],"diver-based":[28],"surveys":[29],"labor-intensive":[31],"prone":[33],"to":[34,71,87,175,199,236,286,332],"missed":[35],"detections,":[36],"motivating":[37],"automated":[38],"detection":[39,45,148],"from":[40,181],"underwater":[41,48,75,336],"imagery.":[42],"However,":[43],"COTS":[44,56,104,179],"in":[46,162,171,299],"complex":[47,78],"scenes":[49],"still":[50],"faces":[51],"three":[52,143,260],"major":[53],"challenges.":[54],"First,":[55],"individuals":[57],"often":[59],"very":[60],"small":[61,155],"carry":[63],"limited":[64],"discriminative":[65],"information,":[66],"them":[68],"inherently":[69],"difficult":[70],"detect.":[72],"Second,":[73],"low":[74],"contrast":[76],"textures":[80],"blur":[81],"target":[82],"boundaries":[83],"cause":[85],"targets":[86,180],"be":[88],"easily":[89],"confused":[90],"with":[91],"background.":[93],"Third,":[94],"ecological":[95,337],"values":[97],"recall":[98,115,201],"more":[99,108],"highly":[100],"than":[101,110,313],"precision\u2014missing":[102],"individual":[105],"is":[106,308],"far":[107],"costly":[109],"false":[112,276],"alarm\u2014yet":[113],"existing":[117],"detectors":[118,331],"remains":[119],"insufficient.":[120],"To":[121],"address":[122],"these":[123],"challenges,":[124],"we":[125],"propose":[126],"HiFi-Det":[127,141,212],"(High-resolution":[128],"Frequency-integration":[129],"Detector),":[130],"collaborative":[132],"multi-scale":[133],"frequency-domain":[134],"feature":[135,152],"optimization":[136],"method":[137],"built":[138],"on":[139,196],"YOLO11.":[140],"integrates":[142],"complementary":[144],"enhancements:":[145],"high-resolution":[147,263],"branch":[149,264],"that":[150,167,193,243,297,305,321],"strengthens":[151],"representation":[153],"targets;":[156],"wavelet":[157,173],"transform":[158],"convolution":[159],"(WTConv)":[160],"modules":[161],"backbone":[164,290,298],"neck":[166],"apply":[168],"band-separated":[169],"processing":[170],"domain":[174],"improve":[176,200],"discrimination":[177],"low-contrast,":[182],"textured":[183],"backgrounds;":[185],"WIoUv3":[188,273],"bounding":[189],"box":[190],"regression":[191],"loss":[192],"dynamically":[194],"focuses":[195],"ordinary-quality":[197],"samples":[198],"while":[202,228,278],"maintaining":[203],"precision.":[204],"On":[205],"public":[207],"Great":[208],"Barrier":[209],"Reef":[210],"dataset,":[211],"attains":[213],"81.02%":[214],"F2":[215,301],"87.54%":[217],"mAP@50,":[218],"surpassing":[219],"YOLO11":[221],"baseline":[222,239],"by":[223],"3.00%":[224],"2.57%,":[226],"respectively,":[227],"keeping":[229],"parameter":[231],"count":[232],"essentially":[233],"unchanged":[234],"relative":[235],"YOLO11s":[238],"(within":[240],"3%),":[241],"so":[242],"accuracy":[245],"gains":[246],"obtained":[248],"without":[249],"inflating":[250],"model":[251],"size.":[252],"Ablation":[253],"studies":[254],"confirm":[255],"synergy":[257],"components:":[261],"preserves":[265],"spatial":[266],"details,":[267],"WTConv":[268],"suppresses":[269],"background":[270],"textures,":[271],"further":[274],"curbs":[275],"positives":[277],"sustaining":[279],"high":[280],"recall.":[281],"Applying":[282],"same":[284],"recipe":[285,311],"larger":[288],"YOLO11m":[289],"yields":[291],"HiFi-Det-m,":[292],"which":[293],"likewise":[294],"improves":[295],"over":[296],"both":[300],"recall,":[303],"indicating":[304],"approach":[307],"transferable":[310],"rather":[312],"single":[315],"fixed":[316],"architecture.":[317],"These":[318],"results":[319],"show":[320],"task-specific":[322],"architectural":[323],"training":[325],"designs":[326],"can":[327],"effectively":[328],"adapt":[329],"generic":[330],"demands":[334],"monitoring.":[338]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2026-08-18T00:00:00"}