dc.contributor.author | Kechagias-Stamatis, Odysseas | |
dc.contributor.author | Aouf, Nabil | |
dc.contributor.author | Belloni, Carole D. L. | |
dc.date.accessioned | 2019-05-02T18:52:09Z | |
dc.date.available | 2019-05-02T18:52:09Z | |
dc.date.issued | 2018-05-28 | |
dc.identifier.citation | O Kechagias-Stamatis, N Aouf and CDL Belloni. SAR automatic target recognition based on convolutional neural networks. In: IET International Conference on Radar Systems (Radar 2017), Belfast, 23-26 October 2017 | en_UK |
dc.identifier.isbn | 978-1-78561-673-0 | |
dc.identifier.uri | 10.1049/cp.2017.0437 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/8367522 | |
dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/14127 | |
dc.description.abstract | We propose a multi-modal multi-discipline strategy appropriate for Automatic Target Recognition (ATR) on Synthetic Aperture Radar (SAR) imagery. Our architecture relies on a pre-trained, in the RGB domain, Convolutional Neural Network that is innovatively applied on SAR imagery, and is combined with multiclass Support Vector Machine classification. The multi-modal aspect of our architecture enforces the generalisation capabilities of our proposal, while the multi-discipline aspect bridges the modality gap. Even though our technique is trained in a single depression angle of 17°, average performance on the MSTAR database over a 10-class target classification problem in 15°, 30° and 45° depression is 97.8%. This multi-target and multi-depression ATR capability has not been reported yet in the MSTAR database literature. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | IEEE | en_UK |
dc.rights | Attribution-NonCommercial 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
dc.subject | Automatic Target recognition | en_UK |
dc.subject | Convolutional Neural Networks | en_UK |
dc.subject | Deep Learning | en_UK |
dc.subject | Support Vector Machine | en_UK |
dc.subject | Synthetic Aperture Radar | en_UK |
dc.title | SAR automatic target recognition based on convolutional neural networks | en_UK |
dc.type | Conference paper | en_UK |
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