It is clear that the learning effectiveness and learning speed of neural networks are in
general far slower than required, which has been a major bottleneck for many applications. …

Cheese making has been inferred at several sites in northern Europe as early as the 6th
millennium BC and was common in Egypt and Mesopotamia in 3rd millennium BC. However, …

The explosive growth and widespread accessibility of digital health data have led to a surge
of research activity in the healthcare and data sciences fields. The conventional approaches …

Cannabis is one of the oldest cultivated plants in East Asia, grown for grain and fiber as well
as for recreational, medical, and ritual purposes. It is one of the most widely used …

As demonstrated earlier, the learning effectiveness and learning speed of single-hidden-layer
feedforward neural networks are in general far slower than required, which has been a …

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 …

The extreme learning machine (ELM), which was originally proposed for “generalized”
single-hidden layer feedforward neural networks, provides efficient unified learning solutions for …

In the Vehicular Ad hoc Networks (VANET) environment, recognizing traffic accident events
in the driving videos captured by vehicle-mounted cameras is an essential task. Generally, …

With the proliferation of online services and mobile technologies, the world has stepped into
a multimedia big data era. A vast amount of research work has been done in the multimedia …

Rails are among the most important components of railway transportation, and real-time
defects detection of the railway is an important and challenging task because of intensity …