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In this paper, we propose a phase field variational model with arctangent regularization for saliency detection. The classical Cahn-Hilliard model is used to extract features in complex image domain with highly anisotropic interfacial energy. Various visual attention features can be detected by minimizing the energy functional. The processing of saliency detection can be seen as a dynamical competition...
This paper considers the problem of material recognition. Motivated by observation of close interconnections between material and object recognition, we study how to select and integrate multiple features obtained by different models of Convolutional Neural Networks (CNNs) trained in a transfer learning setting. To be specific, we first compute activations of features using representations on images...
A novel non-Newtonian fluid simulation method for SPH is proposed in this article. The viscous liquid is modeled by a non-Newtonian fluid flow, and the variable viscosity under shear stress is achieved using a viscosity model known as Cross model. To avoid tensile instability and improve numerical stability, a predictive-corrective method, aimed at correcting density error, of setting up individual...
This paper presents an algorithmic approach for improving the performance of many types of stochastic dynamical simulations. The approach is to redesign existing algorithms that use sparse matrix-vector products (SPMV) with single vectors to instead use a more efficient kernel, the generalized SPMV (GSPMV), which computes with multiple vectors simultaneously. In this paper, we show how to redesign...
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