Target recognition for synthetic aperture radar imagery based on convolutional neural network feature fusion

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dc.contributor.authorKechagias-Stamatis, Odysseas
dc.date.accessioned2019-02-13T14:50:16Z
dc.date.available2019-02-13T14:50:16Z
dc.date.issued2018-12-04
dc.description.abstractDriven by the great success of deep convolutional neural networks (CNNs) that are currently used by quite a few computer vision applications, we extend the usability of visual-based CNNs into the synthetic aperture radar (SAR) data domain without employing transfer learning. Our SAR automatic target recognition (ATR) architecture efficiently extends the pretrained Visual Geometry Group CNN from the visual domain into the X-band SAR data domain by clustering its neuron layers, bridging the visual—SAR modality gap by fusing the features extracted from the hidden layers, and by employing a local feature matching scheme. Trials on the moving and stationary target acquisition dataset under various setups and nuisances demonstrate a highly appealing ATR performance gaining 100% and 99.79% in the 3-class and 10-class ATR problem, respectively. We also confirm the validity, robustness, and conceptual coherence of the proposed method by extending it to several state-of-the-art CNNs and commonly used local feature similarity/match metrics.en_UK
dc.identifier.citationKechagias-Stamatis O., Target recognition for synthetic aperture radar imagery based on convolutional neural network feature fusion, Journal of Applied Remote Sensing, Volume 12, Issue number 4, 2018, Article No. 046025.en_UK
dc.identifier.issn1931-3195
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/13900
dc.language.isoenen_UK
dc.publisherSPIEen_UK
dc.relation.ispartofseries;046025
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectAutomatic Target Recognitionen_UK
dc.subjectConvolutional Neural Networksen_UK
dc.subjectDeep Learningen_UK
dc.subjectSynthetic Aperture Radaren_UK
dc.titleTarget recognition for synthetic aperture radar imagery based on convolutional neural network feature fusionen_UK
dc.typeArticleen_UK

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