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As the Internet of Vehicles and cloud computing have rapidly developed, they have become increasingly relevant to the online prediction of the state of health (SOH) of lithium‐ion batteries (LIBs). To accurately and robustly predict the SOH of LIBs within a variable voltage range, a novel intelligent SOH prediction model for LIBs is proposed by combining a one‐dimensional convolutional (Conv1D) layer,...
In this paper, we present a scene interpretation framework for Synthetic Aperture Radar (SAR) images, using keywords of the image contents provided by users. The framework consists of incorporation of prior knowledge with SAR iMage Annotation Tool (SARMAT), representation of SAR images, and prediction of scene labels based on the supervised Latent Dirichlet Allocation (sLDA) model. The experiment...
In this paper, we present a novel urban area extraction method for High Resolution (HR) Synthetic Aperture Radar (SAR) images based on an iterated Foreground/Background Separation (iFBS) framework. The performance of the proposed approach is presented and analyzed on a TerraSAR-X HR SAR experimental data set.
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