Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …

In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …

In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …

The camera provides rich visual information regarding objects and becomes one of the most
mainstream sensors in the automation community. However, it is often difficult to be …

Recent research has shown the speed advantage of extreme learning machine (ELM) and
the accuracy advantage of sparse representation classification (SRC) in the area of image …

Detecting unknown malware and their variants remains both an operational challenge and a
research challenge. In recent years, there have been attempts to design machine learning …

This paper addresses a finite-time H∞ fuzzy control problem for a class of nonlinear
Markovian jump delayed systems with partly uncertain transition descriptions, which is …

Emotions play a crucial role in decision-making, brain activity, human cognition, and social
intercourse. This paper proposes a hierarchical network structure with subnetwork nodes to …

Due to its much faster speed and better generalization performance, extreme learning
machine (ELM) has attracted much attention as an effective learning approach. However …

As stock data is characterized by highly noisy and non-stationary, stock price prediction is
regarded as a knotty problem. In this paper, we propose new two-stage ensemble models by …