{"id":"https://openalex.org/W3131890988","doi":"https://doi.org/10.1109/lra.2021.3058911","title":"Elevation Angle Estimation in 2D Acoustic Images Using Pseudo Front View","display_name":"Elevation Angle Estimation in 2D Acoustic Images Using Pseudo Front View","publication_year":2021,"publication_date":"2021-02-13","ids":{"openalex":"https://openalex.org/W3131890988","doi":"https://doi.org/10.1109/lra.2021.3058911","mag":"3131890988"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2021.3058911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3058911","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","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/A5083170179","display_name":"Yusheng Wang","orcid":"https://orcid.org/0000-0002-8665-3437"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusheng Wang","raw_affiliation_strings":["Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-8665-3437","affiliations":[{"raw_affiliation_string":"Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090163777","display_name":"Yonghoon Ji","orcid":"https://orcid.org/0000-0002-0828-6627"},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yonghoon Ji","raw_affiliation_strings":["Graduate School for Advanced Science and Technology, Japan Advanced Institute of Science and Technology, Ishikawa, Japan"],"raw_orcid":"https://orcid.org/0000-0002-0828-6627","affiliations":[{"raw_affiliation_string":"Graduate School for Advanced Science and Technology, Japan Advanced Institute of Science and Technology, Ishikawa, Japan","institution_ids":["https://openalex.org/I177738480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019431013","display_name":"Dingyu Liu","orcid":"https://orcid.org/0000-0003-4563-6056"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Dingyu Liu","raw_affiliation_strings":["Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-4563-6056","affiliations":[{"raw_affiliation_string":"Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100866983","display_name":"Hiroshi Tsuchiya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hiroshi Tsuchiya","raw_affiliation_strings":["Research Institute, Wakachiku Construction Company, Ltd., Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute, Wakachiku Construction Company, Ltd., Chiba, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021260328","display_name":"Atsushi Yamashita","orcid":"https://orcid.org/0000-0003-1280-069X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Yamashita","raw_affiliation_strings":["Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-1280-069X","affiliations":[{"raw_affiliation_string":"Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064103302","display_name":"Hajime Asama","orcid":"https://orcid.org/0000-0002-9482-497X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hajime Asama","raw_affiliation_strings":["Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9482-497X","affiliations":[{"raw_affiliation_string":"Department of Precision Engineering, Graduate School of Engineering, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7465,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.86393768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"6","issue":"2","first_page":"1535","last_page":"1542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9986000061035156,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9986000061035156,"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":0.9983000159263611,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9980999827384949,"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/dimension","display_name":"Dimension (graph theory)","score":0.663364052772522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6628196835517883},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.6550076603889465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6207765340805054},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6046528816223145},{"id":"https://openalex.org/keywords/bijection","display_name":"Bijection","score":0.5715020298957825},{"id":"https://openalex.org/keywords/elevation","display_name":"Elevation (ballistics)","score":0.555243968963623},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5443664193153381},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4661045968532562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36782896518707275},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.215691477060318},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11861112713813782},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08848455548286438}],"concepts":[{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.663364052772522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6628196835517883},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.6550076603889465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6207765340805054},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6046528816223145},{"id":"https://openalex.org/C24424167","wikidata":"https://www.wikidata.org/wiki/Q180907","display_name":"Bijection","level":2,"score":0.5715020298957825},{"id":"https://openalex.org/C37054046","wikidata":"https://www.wikidata.org/wiki/Q641888","display_name":"Elevation (ballistics)","level":2,"score":0.555243968963623},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5443664193153381},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4661045968532562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36782896518707275},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.215691477060318},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11861112713813782},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08848455548286438},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2021.3058911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3058911","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","display_name":"Life below water","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1816460154","https://openalex.org/W1901129140","https://openalex.org/W1919081082","https://openalex.org/W2344693513","https://openalex.org/W2476548250","https://openalex.org/W2515288524","https://openalex.org/W2566466113","https://openalex.org/W2587886726","https://openalex.org/W2745659056","https://openalex.org/W2763228906","https://openalex.org/W2765881441","https://openalex.org/W2793723378","https://openalex.org/W2795298767","https://openalex.org/W2891194622","https://openalex.org/W2904379337","https://openalex.org/W2950275448","https://openalex.org/W2962793481","https://openalex.org/W2964121744","https://openalex.org/W2966943864","https://openalex.org/W2998166571","https://openalex.org/W3003384814","https://openalex.org/W3004127223","https://openalex.org/W3009257710","https://openalex.org/W3091717112","https://openalex.org/W3132284905","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6783907636","https://openalex.org/W6791563453"],"related_works":["https://openalex.org/W4287020903","https://openalex.org/W2952259524","https://openalex.org/W2279732055","https://openalex.org/W2995857455","https://openalex.org/W4288805235","https://openalex.org/W2998840281","https://openalex.org/W2027277382","https://openalex.org/W1508013399","https://openalex.org/W3181135859","https://openalex.org/W4302399754"],"abstract_inverted_index":{"A":[0],"novel":[1,87],"method":[2,91,95,153],"to":[3,32,45,100,156],"estimate":[4,113],"the":[5,39,46,51,64,78,81,97,114,119,123,128,137,146,175,178],"missing":[6,47,115],"dimension":[7,48,55,116],"in":[8,17,28,134],"2D":[9,26,75],"acoustic":[10,42,98],"images":[11,27,43],"for":[12,162,169],"3D":[13,72],"reconstruction":[14],"is":[15,56,92,139,154],"proposed":[16,110,179],"this":[18,84],"paper.":[19],"Acoustic":[20],"cameras":[21],"can":[22,112],"acquire":[23],"high":[24],"resolution":[25],"underwater":[29,135],"environment":[30],"insusceptible":[31],"water":[33],"turbidity":[34],"and":[35,74,117,171],"light":[36],"condition.":[37],"However,":[38],"formulation":[40],"of":[41,66,80,122,127,130,177],"leads":[44],"problem.":[49,82],"Estimating":[50],"unknown":[52],"elevation":[53,88],"angle":[54,89],"a":[57,86,105,149,158],"difficult":[58],"task":[59],"which":[60],"has":[61],"recently":[62],"drawn":[63],"attention":[65],"researchers.":[67],"The":[68,94,109],"non-bijective":[69],"characteristic":[70],"between":[71],"points":[73],"pixels":[76],"increases":[77],"complexity":[79],"In":[83],"paper,":[85],"estimation":[90],"proposed.":[93],"transfers":[96],"view":[99,103],"pseudo":[101],"front":[102],"using":[104,141],"deep":[106],"neural":[107,150],"network.":[108],"network":[111,138],"resolve":[118],"non-bijection":[120],"problem":[121],"2D-3D":[124],"correspondence.":[125],"Because":[126],"difficulty":[129],"acquiring":[131],"depth":[132],"information":[133],"environments,":[136],"trained":[140],"simulated":[142],"images.":[143],"To":[144],"mitigate":[145],"sim-real":[147],"gap,":[148],"style":[151],"transfer":[152],"implemented":[155],"generate":[157],"realistic":[159],"image":[160],"dataset":[161],"training.":[163],"Simulation":[164],"experiments":[165],"were":[166],"carried":[167],"out":[168],"evaluation":[170],"real":[172],"data":[173],"proved":[174],"feasibility":[176],"method.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}