{"id":"https://openalex.org/W7134163217","doi":"https://doi.org/10.1049/ipr2.70313","title":"SSGA\u2010YOLO: A Lightweight Sonar Image Object Detection Network With Efficient Convolution and Acoustic\u2010Aware Attention for Embedded Systems","display_name":"SSGA\u2010YOLO: A Lightweight Sonar Image Object Detection Network With Efficient Convolution and Acoustic\u2010Aware Attention for Embedded Systems","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7134163217","doi":"https://doi.org/10.1049/ipr2.70313"},"language":"en","primary_location":{"id":"doi:10.1049/ipr2.70313","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70313","pdf_url":null,"source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1049/ipr2.70313","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128339327","display_name":"Yan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Liu","raw_affiliation_strings":["College of Information Science and Engineering Hohai University  Changzhou China"],"raw_orcid":"https://orcid.org/0000-0001-9887-2795","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering Hohai University  Changzhou China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128337308","display_name":"Gan Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gan Yan","raw_affiliation_strings":["College of Information Science and Engineering Hohai University  Changzhou China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering Hohai University  Changzhou China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100775136","display_name":"Tong Chen","orcid":"https://orcid.org/0000-0003-0173-9352"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Chen","raw_affiliation_strings":["College of Information Science and Engineering Hohai University  Changzhou China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering Hohai University  Changzhou China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081268493","display_name":"Guanying Huo","orcid":"https://orcid.org/0000-0002-2568-8249"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guanying Huo","raw_affiliation_strings":["College of Information Science and Engineering Hohai University  Changzhou China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering Hohai University  Changzhou China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081268493","https://openalex.org/A5128339327"],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":{"value":2000,"currency":"EUR","value_usd":2200},"apc_paid":{"value":2000,"currency":"EUR","value_usd":2200},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42379245,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6280999779701233,"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":0.6280999779701233,"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/T11698","display_name":"Underwater Acoustics Research","score":0.120899997651577,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.07000000029802322,"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/sonar","display_name":"Sonar","score":0.792900025844574},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6108999848365784},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5954999923706055},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5942999720573425},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5483999848365784},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.47049999237060547},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.44679999351501465},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.44589999318122864},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3917999863624573}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8241000175476074},{"id":"https://openalex.org/C555745239","wikidata":"https://www.wikidata.org/wiki/Q133220","display_name":"Sonar","level":2,"score":0.792900025844574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6506999731063843},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6108999848365784},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5954999923706055},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5942999720573425},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5651000142097473},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38280001282691956},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C181255713","wikidata":"https://www.wikidata.org/wiki/Q7662740","display_name":"Synthetic aperture sonar","level":3,"score":0.3431999981403351},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3003999888896942},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2696000039577484},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26249998807907104}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1049/ipr2.70313","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70313","pdf_url":null,"source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1049/ipr2.70313","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70313","pdf_url":null,"source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.5814999341964722,"display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G4159973912","display_name":null,"funder_award_id":"62571179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8607689015","display_name":null,"funder_award_id":"U2441254","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2193145675","https://openalex.org/W2601564443","https://openalex.org/W2752782242","https://openalex.org/W2883780447","https://openalex.org/W2884585870","https://openalex.org/W2890326128","https://openalex.org/W2963037989","https://openalex.org/W2966271978","https://openalex.org/W2967441388","https://openalex.org/W2988396473","https://openalex.org/W2992240579","https://openalex.org/W3034971973","https://openalex.org/W3035414587","https://openalex.org/W3036708415","https://openalex.org/W3096609285","https://openalex.org/W3162418282","https://openalex.org/W3195424217","https://openalex.org/W3197086755","https://openalex.org/W3200819120","https://openalex.org/W3206287456","https://openalex.org/W3215128484","https://openalex.org/W4211039209","https://openalex.org/W4221063239","https://openalex.org/W4310742868","https://openalex.org/W4312373555","https://openalex.org/W4313320402","https://openalex.org/W4324116440","https://openalex.org/W4380201099","https://openalex.org/W4386047745","https://openalex.org/W4386071462","https://openalex.org/W4388635207","https://openalex.org/W4393308750","https://openalex.org/W4402656878","https://openalex.org/W4404199198","https://openalex.org/W4405493911","https://openalex.org/W4408582449","https://openalex.org/W4411408117","https://openalex.org/W4415440714"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"To":[1,150],"address":[2],"the":[3,36,70,99,107,120,209,231],"problems":[4],"of":[5,72,101,122,140,206,219],"high":[6,187],"computational":[7,132],"complexity":[8],"and":[9,23,32,54,63,75,106,116,131,142,147,178,198],"limited":[10],"deploy":[11],"ability":[12],"in":[13,78,119,144],"underwater":[14,236],"sonar":[15,30,79,104],"image":[16],"detection,":[17],"we":[18],"propose":[19],"SSGA\u2010YOLO,":[20],"a":[21,49,64,216],"lightweight":[22,65,228],"efficient":[24,85],"object":[25],"detection":[26,100,188],"algorithm":[27],"optimised":[28],"for":[29,84,169,174,180,234],"imagery":[31],"successfully":[33],"deployed":[34],"on":[35,43,162,195,202,222],"Ascend":[37],"AI":[38],"embedded":[39,157],"platform.":[40],"SSGA\u2010YOLO":[41,126,184],"focuses":[42],"three":[44,163],"key":[45,114],"aspects":[46],"to":[47,68,97,135],"achieve":[48],"favourable":[50],"balance":[51],"between":[52],"accuracy":[53],"efficiency.":[55],"The":[56,87],"S\u2010Net":[57],"backbone":[58],"employs":[59],"depthwise":[60],"separable":[61],"convolutions":[62],"attention":[66],"mechanism":[67],"enhance":[69],"extraction":[71],"weak":[73],"echo":[74],"shadow":[76],"features":[77],"images":[80],"while":[81],"reducing":[82],"redundancy":[83],"deployment.":[86],"Efficient":[88],"Group":[89,110],"Shuffle":[90],"Convolution":[91],"(EGSConv)":[92],"enhances":[93],"cross\u2010channel":[94],"feature":[95],"interaction":[96],"improve":[98],"small,":[102],"low\u2010contrast":[103],"targets":[105],"Lightweight":[108],"Shuffle\u2010Aware":[109],"Attention":[111],"(LSGA)":[112],"refines":[113],"acoustic":[115],"spatial":[117],"cues":[118],"presence":[121],"strong":[123],"noise.":[124],"Furthermore,":[125],"significantly":[127],"reduces":[128],"model":[129,152,210],"parameters":[130],"complexity:":[133],"compared":[134],"YOLOv8n,":[136],"it":[137],"achieves":[138,186],"reductions":[139],"79.82%":[141],"74.07%":[143],"parameter":[145],"count":[146],"GFLOPs,":[148],"respectively.":[149],"evaluate":[151],"performance":[153],"across":[154],"diverse":[155],"environments,":[156],"deployment":[158],"experiments":[159],"were":[160],"conducted":[161],"datasets":[164,197],"representing":[165],"distinct":[166],"scenarios:":[167],"MDFD":[168],"controlled":[170],"artificial":[171],"tanks,":[172],"UATD":[173],"complex":[175],"natural":[176],"waters":[177],"MOTfish":[179],"dynamic":[181],"video":[182],"sequences.":[183],"consistently":[185],"accuracy,":[189],"with":[190],"an":[191],"mAP50":[192],"exceeding":[193],"0.930":[194],"all":[196],"peaking":[199],"at":[200],"0.983":[201],"MDFD.":[203],"In":[204],"terms":[205],"inference":[207],"efficiency,":[208],"demonstrates":[211],"exceptional":[212],"real\u2010time":[213],"capability,":[214],"reaching":[215],"frame":[217],"rate":[218],"65.77":[220],"FPS":[221],"MOTfish.":[223],"These":[224],"results":[225],"outperform":[226],"other":[227],"detectors,":[229],"confirming":[230],"model's":[232],"effectiveness":[233],"practical":[235],"applications.":[237]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-09T00:00:00"}
