{"id":"https://openalex.org/W4285158235","doi":"https://doi.org/10.1109/tits.2022.3168806","title":"Reliable Object Recognition Using Deep Transfer Learning for Marine Transportation Systems With Underwater Surveillance","display_name":"Reliable Object Recognition Using Deep Transfer Learning for Marine Transportation Systems With Underwater Surveillance","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285158235","doi":"https://doi.org/10.1109/tits.2022.3168806"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3168806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3168806","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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/A5068225668","display_name":"Mohammad Kazem Moghimi","orcid":"https://orcid.org/0000-0003-0419-9806"},"institutions":[{"id":"https://openalex.org/I180634299","display_name":"University of Sistan and Baluchestan","ror":"https://ror.org/02n43xw86","country_code":"IR","type":"education","lineage":["https://openalex.org/I180634299"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Kazem Moghimi","raw_affiliation_strings":["Department of Communication Engineering, University of Sistan and Baluchestan, Zahedan 9816745845, Iran"],"raw_orcid":"https://orcid.org/0000-0003-0419-9806","affiliations":[{"raw_affiliation_string":"Department of Communication Engineering, University of Sistan and Baluchestan, Zahedan 9816745845, Iran","institution_ids":["https://openalex.org/I180634299"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038071551","display_name":"Farahnaz Mohanna","orcid":"https://orcid.org/0000-0002-8689-6201"},"institutions":[{"id":"https://openalex.org/I180634299","display_name":"University of Sistan and Baluchestan","ror":"https://ror.org/02n43xw86","country_code":"IR","type":"education","lineage":["https://openalex.org/I180634299"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Farahnaz Mohanna","raw_affiliation_strings":["Department of Communication Engineering, University of Sistan and Baluchestan, Zahedan 9816745845, Iran"],"raw_orcid":"https://orcid.org/0000-0002-8689-6201","affiliations":[{"raw_affiliation_string":"Department of Communication Engineering, University of Sistan and Baluchestan, Zahedan 9816745845, Iran","institution_ids":["https://openalex.org/I180634299"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180634299"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":3.3145,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93777206,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9984999895095825,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9984999895095825,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9983000159263611,"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":0.9966999888420105,"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/underwater","display_name":"Underwater","score":0.7569319009780884},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7219507694244385},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6772549748420715},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.644739031791687},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6162468194961548},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48533812165260315},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44349026679992676},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3645515441894531},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3042530119419098}],"concepts":[{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.7569319009780884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7219507694244385},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6772549748420715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.644739031791687},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6162468194961548},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48533812165260315},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44349026679992676},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3645515441894531},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3042530119419098},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3168806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3168806","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2102605133","https://openalex.org/W2124211486","https://openalex.org/W2186155590","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2585392941","https://openalex.org/W2615126350","https://openalex.org/W2793188405","https://openalex.org/W2809054032","https://openalex.org/W2831859938","https://openalex.org/W2889983693","https://openalex.org/W2895340641","https://openalex.org/W2954819764","https://openalex.org/W2963037989","https://openalex.org/W2963073398","https://openalex.org/W2966501856","https://openalex.org/W2987988737","https://openalex.org/W2997344004","https://openalex.org/W3008762932","https://openalex.org/W3014286955","https://openalex.org/W3022550689","https://openalex.org/W3025180790","https://openalex.org/W3027362665","https://openalex.org/W3039093196","https://openalex.org/W3049773437","https://openalex.org/W3081729309","https://openalex.org/W3083346469","https://openalex.org/W3091687839","https://openalex.org/W3106850582","https://openalex.org/W3108328895","https://openalex.org/W3110926867","https://openalex.org/W3116949188","https://openalex.org/W3120892490","https://openalex.org/W3136429334","https://openalex.org/W3169767072","https://openalex.org/W3173743304","https://openalex.org/W3185956081","https://openalex.org/W3194026771","https://openalex.org/W3196915239","https://openalex.org/W3202063164","https://openalex.org/W3209004384","https://openalex.org/W3213403031","https://openalex.org/W4200045448","https://openalex.org/W6753322352","https://openalex.org/W6758959859","https://openalex.org/W6765415427"],"related_works":["https://openalex.org/W4388412763","https://openalex.org/W1999583034","https://openalex.org/W3217214504","https://openalex.org/W3168963531","https://openalex.org/W2591930867","https://openalex.org/W2953138830","https://openalex.org/W2773822314","https://openalex.org/W4315498985","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"object":[3],"recognition":[4],"for":[5,44,61,163],"marine":[6,28,48],"persistent":[7],"surveillance":[8,16],"has":[9,265],"attracted":[10],"much":[11],"attention":[12],"from":[13,206,213],"researchers.":[14],"The":[15,121,170,194],"videos":[17,43],"are":[18,30,67,217],"captured":[19],"with":[20,104,132,152],"using":[21,219],"optical":[22,54,72],"sensors":[23],"in":[24,70,82,173,253,271],"shallow-deep":[25],"water":[26],"where":[27],"vehicles":[29,38],"moving,":[31],"e.g.,":[32],"ships,":[33],"submarines,":[34],"and":[35,47,80,87,101,109,127,226],"underwater":[36,53,62,71,91,111,164,189],"unmanned":[37],"(UUVs).":[39],"Access":[40],"to":[41,115,167,186,201,228,239],"efficient":[42],"maritime":[45],"control":[46],"transportation":[49],"system":[50],"(MTS),":[51],"particularly":[52],"videos,":[55],"is":[56,113,150,177,237],"still":[57],"a":[58,95,99,140,156,180,266],"critical":[59],"demand":[60],"tourism":[63],"industry.":[64],"As":[65],"there":[66],"serious":[68],"problems":[69],"video":[73,130,192,208],"imaging":[74],"systems":[75],"such":[76],"as":[77,139],"light":[78],"scattering":[79],"absorption":[81],"water,":[83],"low":[84],"contrast,":[85],"fog":[86],"haziness,":[88],"detecting":[89,108],"various":[90,136],"objects":[92,112,190],"will":[93],"be":[94],"difficult":[96],"task.":[97],"Moreover,":[98,210],"reliable":[100],"safe":[102],"MTS":[103],"the":[105,117,153,174,198,203,207,214,230,241,246,254,262],"capability":[106],"of":[107,119,135,145,155,245,269],"recognizing":[110],"required":[114],"reduce":[116],"costs":[118],"movements.":[120],"current":[122],"study":[123],"addresses":[124],"predictive":[125],"challenges":[126],"evaluates":[128],"many":[129],"frames":[131],"poor":[133],"qualities":[134],"aquatic":[137],"species":[138],"real":[141,272],"dataset.":[142],"Intelligent":[143],"processing":[144],"vision":[146],"computing-related":[147],"extracted":[148,212],"features":[149,211],"performed":[151],"aid":[154],"modified":[157,181],"convolutional":[158],"neural":[159,183],"network":[160,184],"(CNN)":[161],"architecture":[162],"IoT":[165],"platforms":[166],"support":[168,247],"MTS.":[169],"decision-making":[171],"structure":[172,216],"proposed":[175,255,263],"method":[176],"based":[178],"on":[179],"residual":[182],"(mResNet)":[185],"recognize":[187],"trained":[188],"through":[191],"frames.":[193,209],"mResNet":[195],"approach":[196],"uses":[197],"dilation":[199],"feature":[200,224],"extract":[202],"most":[204],"information":[205],"ResNet":[215],"designed":[218],"traditional":[220],"learning":[221],"approaches":[222],"including":[223],"selection":[225],"classification":[227,267],"identify":[229],"undersea":[231],"objects.":[232],"Also,":[233],"an":[234],"optimization":[235],"process":[236],"employed":[238],"find":[240],"best":[242],"kernel":[243],"parameters":[244],"vector":[248],"machine":[249],"(SVM)":[250],"classifier":[251],"used":[252],"structure.":[256],"Our":[257],"experimental":[258],"results":[259],"indicate":[260],"that":[261],"model":[264],"accuracy":[268],"93.51%":[270],"videos.":[273]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}