{"id":"https://openalex.org/W7164888532","doi":"https://doi.org/10.48550/arxiv.2606.14720","title":"AI for Maritime Security: Comparative Evaluation of CNN and Vision Transformer Architectures for Maritime Object Detection","display_name":"AI for Maritime Security: Comparative Evaluation of CNN and Vision Transformer Architectures for Maritime Object Detection","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7164888532","doi":"https://doi.org/10.48550/arxiv.2606.14720"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.14720","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14720","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.14720","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138720259","display_name":"Ismet Gocer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gocer, Ismet","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138733328","display_name":"Zakirul Bhuiayn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhuiayn, Zakirul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138734557","display_name":"Shakeel Ahmad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmad, Shakeel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065521530","display_name":"Raza Hasan","orcid":"https://orcid.org/0000-0002-8089-837X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasan, Raza","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.3343000113964081,"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/T11622","display_name":"Maritime Navigation and Safety","score":0.3343000113964081,"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/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.310699999332428,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1753000020980835,"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/object-detection","display_name":"Object detection","score":0.651199996471405},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6039000153541565},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.567799985408783},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.512499988079071},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5004000067710876},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4731000065803528}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6764000058174133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6608999967575073},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.651199996471405},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6039000153541565},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.567799985408783},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.512499988079071},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4731000065803528},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46209999918937683},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.39899998903274536},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.37709999084472656},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37529999017715454},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3140999972820282},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.14720","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14720","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.14720","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14720","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"aims":[2],"to":[3],"enhance":[4],"maritime":[5,50,174],"security":[6],"by":[7],"using":[8,102],"advanced":[9],"Artificial":[10],"Intelligence":[11],"(AI)":[12],"and":[13,24,66,90,92,110,116,131,157,178],"Computer":[14],"Vision":[15,94],"(CV)":[16],"techniques.":[17],"For":[18],"this":[19,47],"purpose,":[20],"it":[21],"was":[22,56],"designed":[23],"assessed":[25],"intelligent":[26],"object":[27],"detection":[28],"systems":[29,172],"that":[30,123],"can":[31],"detect":[32],"the":[33,38,142,145,153,158,166],"presence":[34],"of":[35,168],"ships":[36],"on":[37,128],"sea":[39],"surface":[40],"under":[41],"different":[42,59],"real-time":[43],"environments.":[44,68],"To":[45],"achieve":[46],"goal,":[48],"a":[49,76,93],"image":[51],"dataset":[52],"with":[53,152],"6,468":[54],"images":[55],"used,":[57],"covering":[58],"weather":[60],"conditions":[61],"like":[62],"cloudy,":[63],"foggy,":[64],"rainy,":[65],"sunny":[67],"Six":[69],"deep":[70],"learning":[71,85],"architectures":[72,136],"were":[73,100],"evaluated,":[74],"including":[75,106],"base":[77],"Convolutional":[78],"Neural":[79],"Network":[80],"(CNN)":[81],"model,":[82],"four":[83],"transfer":[84],"models":[86,99],"(Xception,":[87],"VGG16,":[88],"MobileNetV2,":[89],"EfficientNetV2L),":[91],"Transformer":[95],"(ViT)":[96],"model.":[97],"The":[98,120,163],"compared":[101],"multiple":[103],"performance":[104,125],"indicators,":[105],"accuracy,":[107],"Type":[108,111],"I":[109],"II":[112],"errors,":[113],"model":[114,124],"size,":[115],"video":[117,160],"processing":[118,161],"time.":[119,162],"results":[121],"show":[122],"varies":[126],"depending":[127],"computational":[129],"constraints":[130],"deployment":[132],"conditions.":[133],"While":[134],"lightweight":[135],"are":[137],"suitable":[138],"for":[139,173],"resource-limited":[140],"devices,":[141],"ViT":[143],"achieved":[144],"best":[146],"overall":[147],"performance,":[148],"reaching":[149],"100%":[150],"accuracy":[151],"lowest":[154],"error":[155],"rates":[156],"fastest":[159],"findings":[164],"highlight":[165],"potential":[167],"AI-driven":[169],"computer":[170],"vision":[171],"surveillance,":[175],"border":[176],"protection,":[177],"autonomous":[179],"navigation.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-17T00:00:00"}