{"id":"https://openalex.org/W4416582682","doi":"https://doi.org/10.1109/tits.2025.3628677","title":"RSOS-Net: Real-Time Surface Obstacle Segmentation Network for Uncrewed Waterborne Vehicles","display_name":"RSOS-Net: Real-Time Surface Obstacle Segmentation Network for Uncrewed Waterborne Vehicles","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W4416582682","doi":"https://doi.org/10.1109/tits.2025.3628677"},"language":null,"primary_location":{"id":"doi:10.1109/tits.2025.3628677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3628677","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5058107332","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0003-1745-1425"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ning Wang","raw_affiliation_strings":["School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069597548","display_name":"Yuan Feng","orcid":"https://orcid.org/0009-0002-2076-5871"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Feng","raw_affiliation_strings":["School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086514721","display_name":"Lixin Tian","orcid":"https://orcid.org/0000-0003-4817-8580"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Tian","raw_affiliation_strings":["School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101769621","display_name":"Yi Wei","orcid":"https://orcid.org/0000-0001-8383-0795"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wei","raw_affiliation_strings":["School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Engineering, the State Key Laboratory of Maritime Technology and Safety, and the Dalian Key Laboratory of Green Power Control and Test for Intelligent Ships, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058107332"],"corresponding_institution_ids":["https://openalex.org/I43313876"],"apc_list":null,"apc_paid":null,"fwci":1.288,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85186823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"27","issue":"1","first_page":"1052","last_page":"1065"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.8671000003814697,"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"}},"topics":[{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.8671000003814697,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.037700001150369644,"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":0.012900000438094139,"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/obstacle","display_name":"Obstacle","score":0.8740000128746033},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.8009999990463257},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.723800003528595},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6686000227928162},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6669999957084656},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6377999782562256},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5196999907493591}],"concepts":[{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.8740000128746033},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.8009999990463257},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.723800003528595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7016000151634216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6858000159263611},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6765000224113464},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6686000227928162},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6669999957084656},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6377999782562256},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48570001125335693},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42640000581741333},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26030001044273376},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3628677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3628677","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1955701043","https://openalex.org/W2044328399","https://openalex.org/W2194775991","https://openalex.org/W2296195675","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2787889241","https://openalex.org/W2811030020","https://openalex.org/W2886934227","https://openalex.org/W2910194729","https://openalex.org/W2910628332","https://openalex.org/W2942504704","https://openalex.org/W2955923365","https://openalex.org/W2963163009","https://openalex.org/W2963351448","https://openalex.org/W2963418739","https://openalex.org/W2963881378","https://openalex.org/W2964217532","https://openalex.org/W2978122847","https://openalex.org/W2982083293","https://openalex.org/W3003522438","https://openalex.org/W3080711308","https://openalex.org/W3135933983","https://openalex.org/W3169865585","https://openalex.org/W3173433277","https://openalex.org/W3181199966","https://openalex.org/W3186318472","https://openalex.org/W3196904463","https://openalex.org/W3204885083","https://openalex.org/W3213331511","https://openalex.org/W4206494026","https://openalex.org/W4226176436","https://openalex.org/W4285251967","https://openalex.org/W4312688875","https://openalex.org/W4312883148","https://openalex.org/W4312974603","https://openalex.org/W4313188982","https://openalex.org/W4319336162","https://openalex.org/W4365801712","https://openalex.org/W4377145686","https://openalex.org/W4379882544","https://openalex.org/W4385975653","https://openalex.org/W4386065453","https://openalex.org/W4386590125","https://openalex.org/W4389554109","https://openalex.org/W4390872037","https://openalex.org/W4391770072","https://openalex.org/W4393066113","https://openalex.org/W4393768623","https://openalex.org/W4394002325","https://openalex.org/W4394862577","https://openalex.org/W4396782878","https://openalex.org/W4398226326","https://openalex.org/W4399619311","https://openalex.org/W4399665657","https://openalex.org/W4400035744","https://openalex.org/W4402195140","https://openalex.org/W4405934321"],"related_works":[],"abstract_inverted_index":{"Due":[0],"to":[1,42,60,106],"water-surface":[2,19,78],"reflection,":[3],"wake":[4],"and":[5,65,86,98,116,139],"sun":[6,110],"glitter,":[7],"an":[8,148,167],"uncrewed":[9],"waterborne":[10],"vehicle":[11],"(UWV)":[12],"faces":[13],"a":[14,33,48],"long-standing":[15],"challenge":[16],"in":[17,178],"identifying":[18],"obstacles":[20,108],"especially":[21],"with":[22,186],"small-scale":[23],"appearance.":[24],"In":[25],"this":[26],"paper,":[27],"inspired":[28],"by":[29,77,112,130],"the":[30,51,80,102,124,145,154,158,173,179],"encoder-decoder":[31],"architecture,":[32],"real-time":[34],"surface":[35],"obstacle":[36],"segmentation":[37],"network":[38,56],"(RSOS-Net)":[39],"is":[40,58,104],"created":[41],"enable":[43],"online":[44],"surface-obstacle":[45],"detection":[46,159],"for":[47],"UWV.":[49],"Primarily,":[50],"improved":[52],"lightweight":[53,96],"feature":[54,88],"pyramid":[55,82],"structure":[57],"deployed":[59],"flexibly":[61],"accommodate":[62],"significant":[63],"scale-variations":[64],"enhance":[66],"focus":[67],"on":[68,153,166],"small":[69],"obstacles,":[70],"simultaneously.":[71],"To":[72],"address":[73],"visual":[74],"ambiguities":[75],"caused":[76],"disturbances,":[79],"fast":[81],"pooling":[83],"module":[84,90],"(FPPM)":[85],"attention-based":[87],"fusion":[89],"(AFFM)":[91],"are":[92],"holistically":[93],"devised":[94],"within":[95],"encoder":[97],"decoder,":[99],"respectively.":[100],"Accordingly,":[101],"FPPM":[103],"able":[105],"distinguish":[107],"from":[109],"glitters":[111],"capturing":[113],"both":[114],"local":[115],"global":[117],"contextual":[118],"information":[119],"via":[120],"cascaded":[121],"pooling,":[122],"while":[123,157],"AFFM":[125],"can":[126],"rule":[127],"out":[128],"reflections":[129],"virtue":[131],"of":[132,151],"channel-spatial":[133],"attention":[134],"mechanism":[135],"augmenting":[136],"detailed":[137],"features":[138],"spatial":[140],"locations.":[141],"Results":[142],"show":[143],"that":[144],"RSOS-Net":[146,174],"achieves":[147],"F1":[149],"score":[150],"65.1%":[152],"LaRS":[155],"dataset,":[156],"speed":[160],"reaches":[161],"79.5":[162],"frames":[163],"per":[164],"second":[165],"NVIDIA":[168],"RTX":[169],"3060":[170],"platform.":[171],"Notably,":[172],"secured":[175],"first":[176],"place":[177],"3rd":[180],"USV-based":[181],"Embedded":[182],"Obstacle":[183],"Segmentation":[184],"Challenge,":[185],"official":[187],"results":[188],"available":[189],"at":[190],"<uri":[191],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[192],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://macvi.org/workshop/macvi25/summary</uri>":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-25T00:00:00"}
