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Infrared Target Detection using Shallow CNNs

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dc.contributor.author Uzun, Engin
dc.contributor.author Aksoy, Tolga
dc.contributor.author Akagündüz, Erdem
dc.date.accessioned 2022-05-27T10:40:02Z
dc.date.available 2022-05-27T10:40:02Z
dc.date.issued 2020
dc.identifier.citation Uzun, Engin; Aksoy, Tolga; Akagündüz, Erdem (2020). "Infrared Target Detection using Shallow CNNs", 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings, Gaziantep, 5 October 2020. tr_TR
dc.identifier.isbn 9781728172064
dc.identifier.uri http://hdl.handle.net/20.500.12416/5586
dc.description.abstract Convolutional Neural Networks can solve the target detection problem satisfactorily. However, the proposed solutions generally require deep networks and hence, are inefficient when it comes to utilising them on performance-limited systems. In this paper, we study the infrared target detection problem using a shallow network solution, accordingly its implementation on a performance limited system. Using a dataset comprising real and simulated infrared scenes; it is observed that, when trained with the correct training strategy, shallow networks can provide satisfactory performance, even with scale-invariance capability. © 2020 IEEE. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1109/SIU49456.2020.9302501 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Infrared Target Detection tr_TR
dc.subject Shallow Networks tr_TR
dc.subject Two Step Learning tr_TR
dc.title Infrared Target Detection using Shallow CNNs tr_TR
dc.title.alternative Sığ Evrişimli Ağlar ile Kızıl Ötesi Hedef Tespiti tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings tr_TR
dc.contributor.authorID 233834 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü tr_TR


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