{"id":"https://openalex.org/W4377041886","doi":"https://doi.org/10.3390/s23104789","title":"Towards Smaller and Stronger: An Edge-Aware Lightweight Segmentation Approach for Unmanned Surface Vehicles in Water Scenarios","display_name":"Towards Smaller and Stronger: An Edge-Aware Lightweight Segmentation Approach for Unmanned Surface Vehicles in Water Scenarios","publication_year":2023,"publication_date":"2023-05-16","ids":{"openalex":"https://openalex.org/W4377041886","doi":"https://doi.org/10.3390/s23104789","pmid":"https://pubmed.ncbi.nlm.nih.gov/37430704"},"language":"en","primary_location":{"id":"doi:10.3390/s23104789","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23104789","pdf_url":"https://www.mdpi.com/1424-8220/23/10/4789/pdf?version=1684227016","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/10/4789/pdf?version=1684227016","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008832023","display_name":"Wei Han","orcid":"https://orcid.org/0000-0001-8308-6169"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]},{"id":"https://openalex.org/I4210157899","display_name":"China State Shipbuilding (China)","ror":"https://ror.org/04rveb346","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210157899"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Han","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","Systems Engineering Research Institute, China State Shipbuilding Corporation, Beijing 100094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"Systems Engineering Research Institute, China State Shipbuilding Corporation, Beijing 100094, China","institution_ids":["https://openalex.org/I4210157899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018280302","display_name":"Binyu Zhao","orcid":"https://orcid.org/0000-0002-9564-6757"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binyu Zhao","raw_affiliation_strings":["School of Computer Science and Techonogy, Harbin Institute of Technology, Harbin 150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Techonogy, Harbin Institute of Technology, Harbin 150001, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016769551","display_name":"Jun Luo","orcid":"https://orcid.org/0000-0003-1314-5631"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Luo","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008832023"],"corresponding_institution_ids":["https://openalex.org/I113940042","https://openalex.org/I4210157899"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.6695,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62599711,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"23","issue":"10","first_page":"4789","last_page":"4789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9976999759674072,"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":0.9976999759674072,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9955999851226807,"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":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7696493268013},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7506368160247803},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7137925624847412},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6836973428726196},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6313430666923523},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6231764554977417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5624231696128845},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5404710173606873},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4649074971675873},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.43303224444389343},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4211198091506958},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3963415026664734},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.396165132522583},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39288264513015747},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33070695400238037},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12152266502380371},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08040547370910645}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7696493268013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506368160247803},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7137925624847412},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6836973428726196},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6313430666923523},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6231764554977417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5624231696128845},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5404710173606873},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4649074971675873},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.43303224444389343},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4211198091506958},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3963415026664734},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.396165132522583},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39288264513015747},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33070695400238037},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12152266502380371},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08040547370910645},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23104789","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23104789","pdf_url":"https://www.mdpi.com/1424-8220/23/10/4789/pdf?version=1684227016","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:37430704","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37430704","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10224431","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10224431","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10224431/pdf/sensors-23-04789.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:9e91bc1f7c2b4f71aa709125e3ba5d88","is_oa":true,"landing_page_url":"https://doaj.org/article/9e91bc1f7c2b4f71aa709125e3ba5d88","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,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 10, p 4789 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/10/4789/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23104789","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 23; Issue 10; Pages: 4789","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23104789","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23104789","pdf_url":"https://www.mdpi.com/1424-8220/23/10/4789/pdf?version=1684227016","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4377041886.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1910619957","https://openalex.org/W1930528368","https://openalex.org/W2044328399","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2132067725","https://openalex.org/W2167222293","https://openalex.org/W2183341477","https://openalex.org/W2345644119","https://openalex.org/W2521268865","https://openalex.org/W2558027072","https://openalex.org/W2592939477","https://openalex.org/W2886934227","https://openalex.org/W2910194729","https://openalex.org/W2912809890","https://openalex.org/W2963163009","https://openalex.org/W2963307106","https://openalex.org/W2963351448","https://openalex.org/W2963918968","https://openalex.org/W2964350391","https://openalex.org/W2967733054","https://openalex.org/W2970971581","https://openalex.org/W2981637362","https://openalex.org/W2994736168","https://openalex.org/W3003522438","https://openalex.org/W3034609471","https://openalex.org/W3035414587","https://openalex.org/W3035574168","https://openalex.org/W3090912915","https://openalex.org/W3135933983","https://openalex.org/W3139095692","https://openalex.org/W3158725523","https://openalex.org/W3168523553","https://openalex.org/W3169865585","https://openalex.org/W3173433277","https://openalex.org/W3173807327","https://openalex.org/W3186318472","https://openalex.org/W3213331511","https://openalex.org/W4226435677","https://openalex.org/W6674330103","https://openalex.org/W6682889407","https://openalex.org/W6726393737","https://openalex.org/W6762585180","https://openalex.org/W6797139024","https://openalex.org/W6810964125"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W2067272521"],"abstract_inverted_index":{"The":[0,122],"accurate":[1],"detection":[2,131],"and":[3,29,33,76,142,161],"segmentation":[4,57],"of":[5,14,18,118],"accessible":[6],"surface":[7,19],"regions":[8],"in":[9,49,93,101,127,130,134,140,144],"water":[10,55],"scenarios":[11],"is":[12,70,87,108],"one":[13],"the":[15,31,81,102,111,116],"indispensable":[16],"capabilities":[17],"unmanned":[20],"vehicle":[21],"systems.":[22],"'Most":[23],"existing":[24],"methods":[25],"focus":[26],"on":[27,136,146],"accuracy":[28,160],"ignore":[30],"lightweight":[32,54],"real-time":[34,163],"demands.":[35],"Therefore,":[36],"they":[37],"are":[38,125],"not":[39],"suitable":[40],"for":[41,80],"embedded":[42],"devices,":[43],"which":[44,60,114],"have":[45],"been":[46],"wildly":[47],"applied":[48],"practical":[50],"applications.'":[51],"An":[52],"edge-aware":[53],"scenario":[56],"method":[58],"(ELNet),":[59],"establishes":[61],"a":[62,84],"lighter":[63],"yet":[64],"better":[65,162],"network":[66],"with":[67,96],"lower":[68],"computation,":[69],"proposed.":[71],"ELNet":[72,153],"utilizes":[73],"two-stream":[74],"learning":[75],"edge-prior":[77,106],"information.":[78],"Except":[79],"context":[82],"stream,":[83],"spatial":[85,91],"stream":[86],"expanded":[88],"to":[89,110,157],"learn":[90],"details":[92],"low-level":[94],"layers":[95],"no":[97],"extra":[98],"computation":[99],"cost":[100],"inference":[103],"stage.":[104],"Meanwhile,":[105],"information":[107],"introduced":[109],"two":[112],"streams,":[113],"expands":[115],"perspectives":[117],"pixel-level":[119],"visual":[120],"modeling.":[121],"experimental":[123],"results":[124],"45.21%":[126],"FPS,":[128],"98.5%":[129],"robustness,":[132],"75.1%":[133],"F-score":[135,145],"MODS":[137],"benchmark,":[138],"97.82%":[139],"precision,":[141],"93.96%":[143],"USV":[147],"Inland":[148],"dataset.":[149],"It":[150],"demonstrates":[151],"that":[152],"uses":[154],"fewer":[155],"parameters":[156],"achieve":[158],"comparable":[159],"performance.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
