{"id":"https://openalex.org/W2999346173","doi":"https://doi.org/10.1109/icra40945.2020.9197194","title":"A water-obstacle separation and refinement network for unmanned surface vehicles","display_name":"A water-obstacle separation and refinement network for unmanned surface vehicles","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W2999346173","doi":"https://doi.org/10.1109/icra40945.2020.9197194","mag":"2999346173"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9197194","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9197194","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.01921","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018368394","display_name":"Borja Bovcon","orcid":"https://orcid.org/0000-0001-5132-4150"},"institutions":[{"id":"https://openalex.org/I153976015","display_name":"University of Ljubljana","ror":"https://ror.org/05njb9z20","country_code":"SI","type":"education","lineage":["https://openalex.org/I153976015"]}],"countries":["SI"],"is_corresponding":true,"raw_author_name":"Borja Bovcon","raw_affiliation_strings":["Faculty of Computer and Information Science, University of Ljubljana, Slovenia","University of Ljubljana,Faculty of Computer and Information Science,Slovenia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Science, University of Ljubljana, Slovenia","institution_ids":["https://openalex.org/I153976015"]},{"raw_affiliation_string":"University of Ljubljana,Faculty of Computer and Information Science,Slovenia","institution_ids":["https://openalex.org/I153976015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001632955","display_name":"Matej Kristan","orcid":"https://orcid.org/0000-0002-4252-4342"},"institutions":[{"id":"https://openalex.org/I153976015","display_name":"University of Ljubljana","ror":"https://ror.org/05njb9z20","country_code":"SI","type":"education","lineage":["https://openalex.org/I153976015"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Matej Kristan","raw_affiliation_strings":["Faculty of Computer and Information Science, University of Ljubljana, Slovenia","University of  Ljubljana"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Science, University of Ljubljana, Slovenia","institution_ids":["https://openalex.org/I153976015"]},{"raw_affiliation_string":"University of  Ljubljana","institution_ids":["https://openalex.org/I153976015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018368394"],"corresponding_institution_ids":["https://openalex.org/I153976015"],"apc_list":null,"apc_paid":null,"fwci":0.2944,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54299771,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"9470","last_page":"9476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"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":0.9969000220298767,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9968000054359436,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9966999888420105,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.8559005260467529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7166264057159424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6384613513946533},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6311150789260864},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5986602902412415},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5983254909515381},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5810558795928955},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.5735881328582764},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.565062940120697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.562974214553833},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.44140446186065674},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.43171989917755127},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4156964123249054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34491264820098877},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.16838008165359497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12422484159469604},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07584697008132935}],"concepts":[{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.8559005260467529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7166264057159424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6384613513946533},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6311150789260864},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5986602902412415},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5983254909515381},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5810558795928955},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.5735881328582764},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.565062940120697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.562974214553833},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.44140446186065674},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.43171989917755127},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4156964123249054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34491264820098877},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.16838008165359497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12422484159469604},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07584697008132935},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icra40945.2020.9197194","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9197194","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2001.01921","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.01921","pdf_url":"https://arxiv.org/pdf/2001.01921","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2999346173","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2001.01921","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2001.01921","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.01921","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2001.01921","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.01921","pdf_url":"https://arxiv.org/pdf/2001.01921","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2999346173.pdf","grobid_xml":"https://content.openalex.org/works/W2999346173.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1977934833","https://openalex.org/W1995009551","https://openalex.org/W2044328399","https://openalex.org/W2108598243","https://openalex.org/W2125175513","https://openalex.org/W2127369486","https://openalex.org/W2144513243","https://openalex.org/W2150066425","https://openalex.org/W2152529932","https://openalex.org/W2152813046","https://openalex.org/W2157929363","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2476422535","https://openalex.org/W2536397232","https://openalex.org/W2552331162","https://openalex.org/W2560023338","https://openalex.org/W2613718673","https://openalex.org/W2787889241","https://openalex.org/W2799352588","https://openalex.org/W2799990732","https://openalex.org/W2811030020","https://openalex.org/W2886934227","https://openalex.org/W2897713584","https://openalex.org/W2910194729","https://openalex.org/W2911993024","https://openalex.org/W2942504704","https://openalex.org/W2945719496","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2970974096","https://openalex.org/W3003522438","https://openalex.org/W6620707391","https://openalex.org/W6631943919","https://openalex.org/W6681151457","https://openalex.org/W6748481559","https://openalex.org/W6750749703","https://openalex.org/W6753020195","https://openalex.org/W6754123467","https://openalex.org/W6760866495","https://openalex.org/W6764968544"],"related_works":["https://openalex.org/W2791730295","https://openalex.org/W2105111254","https://openalex.org/W2384387713","https://openalex.org/W3080465666","https://openalex.org/W3005924451","https://openalex.org/W3135934332","https://openalex.org/W3112824075","https://openalex.org/W2981958729","https://openalex.org/W2963359474","https://openalex.org/W3195238612","https://openalex.org/W3167444372","https://openalex.org/W3199994414","https://openalex.org/W2000333277","https://openalex.org/W2995939024","https://openalex.org/W3003175783","https://openalex.org/W2794752916","https://openalex.org/W2973225883","https://openalex.org/W2181573261","https://openalex.org/W3029267566","https://openalex.org/W2887062987"],"abstract_inverted_index":{"Obstacle":[0],"detection":[1,34],"by":[2,72,149],"semantic":[3],"segmentation":[4],"shows":[5],"a":[6,49,54,73,95,130,150,154],"great":[7],"promise":[8],"for":[9],"autonomous":[10],"navigation":[11],"in":[12,28,112,122,133,157],"unmanned":[13],"surface":[14],"vehicles":[15],"(USV).":[16],"However,":[17],"existing":[18],"methods":[19],"suffer":[20],"from":[21,81,90],"poor":[22,33],"estimation":[23],"of":[24,30,35,118],"the":[25,87,91,103,113,116,119,123,146,160],"water":[26,43,67,106],"edge":[27,68],"presence":[29],"visual":[31,88],"ambiguities,":[32],"small":[36],"obstacles":[37],"and":[38,45,57,66,107,136],"high":[39],"false-positive":[40],"rate":[41],"on":[42,111],"reflections":[44],"wakes.":[46],"We":[47],"propose":[48],"new":[50],"deep":[51],"encoder-decoder":[52],"architecture,":[53],"water-obstacle":[55],"separation":[56,104],"refinement":[58],"network":[59],"(WaSR),":[60],"to":[61,101,129],"address":[62],"these":[63],"issues.":[64],"Detection":[65],"accuracy":[69],"are":[70],"improved":[71],"novel":[74,96],"decoder":[75,124],"that":[76,143],"gradually":[77],"fuses":[78],"inertial":[79,82],"information":[80],"measurement":[83],"unit":[84],"(IMU)":[85],"with":[86],"features":[89,109],"encoder.":[92],"In":[93],"addition,":[94],"loss":[97],"function":[98],"is":[99,125],"designed":[100],"increase":[102,156],"between":[105],"obstacle":[108],"early":[110],"network.":[114],"Subsequently,":[115],"capacity":[117],"remaining":[120],"layers":[121],"better":[126],"utilised,":[127],"leading":[128],"significant":[131],"reduction":[132],"false":[134],"positives":[135],"increased":[137],"true":[138],"positives.":[139],"Experimental":[140],"results":[141],"show":[142],"WaSR":[144],"outperforms":[145],"current":[147],"state-of-the-art":[148],"large":[151],"margin,":[152],"yielding":[153],"14%":[155],"F-measure":[158],"over":[159],"second-best":[161],"method.":[162]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}