In real-world recognition/classification tasks, limited by various objective factors, it is usually
difficult to collect training samples to exhaust all classes when training a recognizer or …

Background and objective In this work, we present a systematic review concerning the
recent enabling technologies as a tool to the diagnosis, treatment and better quality of life of …

In the world scenario, concerns with security and privacy regarding computer networks are
always increasing. Computer security has become a necessity due to the proliferation of …

The presence of large numbers of security vulnerabilities in popular feature-rich commodity
operating systems has inspired a long line of work on excluding these operating systems …

Abstract Machine learning has played an essential role in the past decades and has been in
lockstep with the main advances in computer technology. Given the massive amount of data …

In this paper, we propose a novel multiclass classifier for the open-set recognition scenario.
This scenario is the one in which there are no a priori training samples for some classes that …

For accommodating rapidly increasing power demands, power systems are transitioning
from analog systems to systems with increasing digital control and communications …

Feature selection aims to find the most important information from a given set of features. As
this task can be seen as an optimization problem, the combinatorial growth of the possible …

Parkinson's Disease (PD) automatic identification in early stages is one of the most
challenging medicine-related tasks to date, since a patient may have a similar behaviour to …

Presence of exudates on a retina is an early sign of diabetic retinopathy, and automatic
detection of these can improve the diagnosis of the disease. Convolutional Neural Networks …