Early time series classification is a variant of the time series classification task, in which a
label must be assigned to the incoming time series as quickly as possible without …

In many situations, the measurements of a studied phenomenon are provided sequentially,
and the prediction of its class needs to be made as early as possible so as not to incur too …

Computational systems and methods are often being used in biological research, including
the understanding of cancer and the development of treatments. Simulations of tumor growth …

The applications of generative adversarial networks (GANs) have received wide acceptance
in the domain of artificial intelligence, which has significantly opened magnificent research …

Early time series classification (ETSC) is crucial for real-world time-sensitive applications.
This task aims to classify time series data with least timestamps at the desired accuracy …

Alarm flood management is essential for industrial process plant safety and efficiency.
Online “alarm flood classification”(AFC) assigns an observed sequence of alarms to one (of …

Alarm flood classification (AFC) methods are crucial in assisting human operators to identify
and mitigate the overwhelming occurrences of alarm floods in industrial process plants, a …

Deep learning has received spectacular adoption in the domain of artificial intelligence. With
this, many deep learning models have been developed. Generative Adversarial Networks …

Deep learning has received significant acceptance in the wide domain of artificial
intelligence. Generative Adversarial Networks (GANs) are the deep learning models which …