{"id":"https://openalex.org/W4402916972","doi":"https://doi.org/10.1109/icip51287.2024.10647408","title":"Advanced Object Detection in Multibeam Forward-Looking Sonar Images Using Linear Cross-Attention Techniques","display_name":"Advanced Object Detection in Multibeam Forward-Looking Sonar Images Using Linear Cross-Attention Techniques","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402916972","doi":"https://doi.org/10.1109/icip51287.2024.10647408"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10647408","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10647408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035568063","display_name":"Gangqi Chen","orcid":"https://orcid.org/0000-0001-8118-4515"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gangqi Chen","raw_affiliation_strings":["Northwestern Polytechnical University,School of Marine Science and Technology,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,School of Marine Science and Technology,Xi’an,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103138436","display_name":"Zhaoyong Mao","orcid":"https://orcid.org/0000-0001-7446-8077"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyong Mao","raw_affiliation_strings":["Northwestern Polytechnical University Unmanned System Research Institute,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University Unmanned System Research Institute,Xi’an,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081646661","display_name":"Junge Shen","orcid":"https://orcid.org/0000-0002-6563-9206"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junge Shen","raw_affiliation_strings":["Northwestern Polytechnical University Unmanned System Research Institute,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University Unmanned System Research Institute,Xi’an,China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":2.942,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91288854,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1026","last_page":"1031"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9657999873161316,"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"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9657999873161316,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9541000127792358,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9448999762535095,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/sonar","display_name":"Sonar","score":0.7830522060394287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6992565989494324},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6051803231239319},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5306372046470642},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5045968294143677},{"id":"https://openalex.org/keywords/synthetic-aperture-sonar","display_name":"Synthetic aperture sonar","score":0.46804213523864746},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45874151587486267},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.22573551535606384}],"concepts":[{"id":"https://openalex.org/C555745239","wikidata":"https://www.wikidata.org/wiki/Q133220","display_name":"Sonar","level":2,"score":0.7830522060394287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6992565989494324},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6051803231239319},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5306372046470642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5045968294143677},{"id":"https://openalex.org/C181255713","wikidata":"https://www.wikidata.org/wiki/Q7662740","display_name":"Synthetic aperture sonar","level":3,"score":0.46804213523864746},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45874151587486267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.22573551535606384}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10647408","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip51287.2024.10647408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2150209417","https://openalex.org/W2193145675","https://openalex.org/W2567051930","https://openalex.org/W2884561390","https://openalex.org/W2891543155","https://openalex.org/W2901280477","https://openalex.org/W2907352405","https://openalex.org/W2951228273","https://openalex.org/W2982770724","https://openalex.org/W3196098908","https://openalex.org/W4212940068","https://openalex.org/W4283661584","https://openalex.org/W4310742868","https://openalex.org/W4313131431","https://openalex.org/W4379011858","https://openalex.org/W4398756379","https://openalex.org/W6739901393","https://openalex.org/W6750227808","https://openalex.org/W6766978945","https://openalex.org/W6892957254"],"related_works":["https://openalex.org/W2610363864","https://openalex.org/W2159784633","https://openalex.org/W2143131560","https://openalex.org/W2544250077","https://openalex.org/W3093449225","https://openalex.org/W1987798457","https://openalex.org/W3022543425","https://openalex.org/W3197313368","https://openalex.org/W1974561532","https://openalex.org/W2086617181"],"abstract_inverted_index":{"Sonar":[0],"images":[1],"object":[2,44,76],"detection":[3,45],"plays":[4],"a":[5,33,42,54,66,82,102,114,137],"crucial":[6],"role":[7],"in":[8,25,117],"marine":[9],"resource":[10],"exploration":[11],"and":[12,22,96],"defense.":[13],"Existing":[14],"methods":[15],"encounter":[16],"challenges":[17],"arising":[18],"from":[19],"non-rigid,":[20],"deformed":[21,95],"low-resolution":[23,97],"objects":[24],"sonar":[26,61],"images,":[27],"making":[28],"them":[29],"difficult":[30],"to":[31,52,72,80,92,106,113],"build":[32],"stable":[34],"feature":[35,57,68,85],"representation.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,64,100],"present":[41],"novel":[43,67],"method":[46,135],"based":[47],"on":[48,123],"linear":[49,103,109],"cross-attention,":[50],"aiming":[51],"construct":[53,81],"more":[55,83],"robust":[56,84],"representation":[58],"tailored":[59],"for":[60],"objects.":[62,98],"Specifically,":[63],"introduce":[65],"fusion":[69],"network":[70],"designed":[71],"efficiently":[73],"extract":[74],"global":[75],"context.":[77],"It":[78],"helps":[79],"representation,":[86],"effectively":[87],"improving":[88],"the":[89,108,124,129,141],"model\u2019s":[90],"ability":[91],"detect":[93],"non-rigidly":[94],"Moreover,":[99],"propose":[101],"attention":[104],"mechanism":[105],"constitute":[107],"cross-attention":[110],"module,":[111],"leading":[112],"significant":[115],"reduction":[116],"computational":[118],"load.":[119],"Extensive":[120],"experiments":[121],"conducted":[122],"public":[125],"available":[126],"dataset":[127],"demonstrate":[128],"superiority":[130],"of":[131],"our":[132],"approach.":[133],"Our":[134],"surpasses":[136],"1.4":[138],"mAP":[139],"over":[140],"baseline,":[142],"while":[143],"requiring":[144],"comparable":[145],"parameters.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}