Classification algorithms integrated with convolutional neural networks (CNN) display high accuracies in synthetic aperture radar (SAR) image classification. However, their consideration of spatial information is not comprehensive and effective, which causes poor performance edges complex regions. This paper proposes a Markov random field (MRF)-based algorithm for SAR classification fully consi...

Fake news is a serious problem, which has received considerable attention from both industry and academic communities. Over the past years, many fake detection approaches have been introduced, most of existing methods rely on either content or social context dissemination process media platforms. In this work, we propose generic model that able to take into account for identification news. Spec...

Inference-based optimization via simulation, which substitutes Gaussian process (GP) learning for the structural properties exploited in mathematical programming, is a powerful paradigm that has been shown to be remarkably effective problems of modest feasible-region size and decision-variable dimension. The limitation “modest” result computational overhead numerical challenges encountered comp...