Explainable artificial intelligence (XAI) has received great interest in the recent decade, due
to its importance in critical application domains, such as self-driving cars, law, and …

Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …

Computer vision (CV) is a big and important field in artificial intelligence covering a wide
range of applications. Image analysis is a major task in CV aiming to extract, analyze and …

Data-efficient image classification is a challenging task that aims to solve image
classification using small training data. Neural network-based deep learning methods are …

Genetic programming (GP) has been applied to feature learning in image classification and
achieved promising results. However, one major limitation of existing GP-based methods is …

The present study aims to predict the coefficient of performance and thermal energy
consumption of an absorption chiller network, using three widely-used machine learning …

Evolutionary deep learning (EDL) as a hot topic in recent years aims at using evolutionary
computation (EC) techniques to address existing issues in deep learning. Most existing work …

Manifold learning techniques have become increasingly valuable as data continues to grow
in size. By discovering a lower-dimensional representation (embedding) of the structure of a …

Modern classifier systems can effectively classify targets that consist of simple patterns.
However, they can fail to detect hierarchical patterns of features that exist in many real-world …

Exploratory data analysis is a fundamental aspect of knowledge discovery that aims to find
the main characteristics of a dataset. Dimensionality reduction, such as manifold learning, is …