The ability of artificial agents to increment their capabilities when confronted with new data is
an open challenge in artificial intelligence. The main challenge faced in such cases is …

Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …

Online continual learning for image classification studies the problem of learning to classify
images from an online stream of data and tasks, where tasks may include new classes …

In this paper, we propose a novel generative adversarial network (GAN) for 3D point clouds
generation, which is called tree-GAN. To achieve state-of-the-art performance for multi-class …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Deep learning architectures exhibit a critical drop of performance due to catastrophic
forgetting when they are required to incrementally learn new tasks. Contemporary …

Currently, with the increasing number of devices connected to the Internet, search for
network vulnerabilities to attackers has increased, and protection systems have become …

The development of automatic video understanding technology is highly needed due to the
rise of mass video data, like surveillance videos, personal video data. Several methods have …

The aim of this paper is to map agricultural crops by classifying satellite image time series.
Domain experts in agriculture work with crop type labels that are organised in a hierarchical …

Despite decades of research in network traffic analysis and incredible advances in artificial
intelligence, network intrusion detection systems based on machine learning (ML) have yet …