Deep neural networks (DNN) have remarkably progressed in applications involving large
and complex datasets but have been criticized as a black-box. This downside has recently …

This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

In this paper, we propose an elegant solution that is directly addressing the bottlenecks of
the traditional deep learning approaches and offers an explainable internal architecture that …

Computer-aided image analysis for better understanding of images has been time-honored
approaches in the medical computing field. In the conventional machine learning approach …

Glaucoma damages the optical nerve, which sends visual pictures to the brain, and results
in irreversible vision loss. This chronic infection is the second leading cause of permanent …

Numeral recognition plays a crucial role in creating automated systems such as posting
address sorting and license plate recognition. Nowadays, numeral recognition systems …

Biometric technology has received a lot of attention in recent years. One of the most
prevalent biometric traits is the finger-knuckle print (FKP). Because the dorsal region of the …

Detection of anomalous behaviors in data centers is crucial to predictive maintenance and
data safety. With data centers, we mean any computer network that allows users to transmit …

A self-organizing algorithm based on an online cluster and fuzzy sets update algorithm
(OCFU) and fuzzy-classification-based social learning particle swarm optimization (FC …

This chapter provides an all-round picture of the development and advances in the fields of
evolving fuzzy systems (EFS) and evolving neuro-fuzzy systems (ENFS) which have been …