With the development of the fifth‐generation networks and artificial intelligence
technologies, new threats and challenges have emerged to wireless communication system …

As living standards improve, modern products need to meet increasingly diversified and
personalized user requirements. Traditional product design methods fall short due to their …

This study investigated the similarity of the catchments with the k-means clustering method
by using the hydrological response unit (HRU) images of 33 catchments located in the …

Objective. The steady-state visual evoked potential (SSVEP)-based brain–computer
interface has received extensive attention in research due to its simple system, less training …

Sparse subspace clustering (SSC) focuses on revealing data distribution from algebraic
perspectives and has been widely applied to high-dimensional data. The key to SSC is to …

Anomaly event detection has been extensively researched in computer vision in recent
years. Most conventional anomaly event detection methods can only leverage the single …

Imbalanced data can always be observed in our daily life and various practical tasks. A lot of
well-constructed machine learning methodologies may produce ineffective performance …

Deep neural network approaches have made remarkable progress in many machine
learning tasks. However, the latest research indicates that they are vulnerable to adversarial …

With the proposed of Generative Adversarial Networks (GANs), the generative adversarial
models have been extensively studied in recent years. Although probability-based methods …

Predicting crowd flows is important for traffic management and public safety, which is very
challenging as it is affected by many complex factors. In this paper, we propose a novel fine …