Abstract: We thoroughly investigate the asymptotic distribution of sum of multiple signal-to-interference-plus-noise-ratios (SINRs) that could be applied to the outage performance evaluation of ...

Abstract: Convolution neural network is successful in pervasive vision tasks, including label distribution learning, which usually takes the form of learning an injection from the nonlinear visual ...

In response to the problem of inadequate utilization of local information in PolSAR image classification using Vision Transformer in existing studies, this paper proposes a Vision Transformer method ...

Motorized active processes enable changes of chromosome structure during the cell’s life cycle. We put forward two families of motorized chain models and analyze how such motors influence the ...

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

Quasicrystals are intriguing structures that have long-range positional correlations but no periodicity in real space, and typically with rotational symmetries that are ‘forbidden’ in conventional ...

Creating high-quality polygonal meshes which represent the membrane surface of neurons for both visualization and numerical simulation purposes is an important yet nontrivial task, due to their ...

The long-term operation of a railroad usually leads to defects in its rails, axles, fasteners, etc. These problems directly affect the safety of the rail system. Therefore, it is important to ensure ...

Methods that fuse multiple localization microscopy images of a single structure can improve signal-to-noise ratio and resolution, but they generally suffer from template bias or sensitivity to ...

Graph neural networks (GNNs) have been applied with great success across science and engineering, but we do not understand why they work so well. Motivated by ...