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 …

Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

The failure of a rolling bearing may cause the shutdown of mechanical equipment and even
induce catastrophic accidents, resulting in tremendous economic losses and a severely …

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 …

Feature selection aims to reduce the number of features and improve the classification
accuracy, which is an essential step in many real-world problems. Multiple feature subsets …

The data of target detection in remote sensing images are diverse, and the detection results
of some categories with a small number of samples are poor. In order to solve this problem …

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 …

Band selection (BS) is a widely used dimensionality reduction technique for hyperspectral
images. However, most of existing evolutionary algorithms focus on searching a globally …

Genetic programming (GP) has been considerably used for image classification because of
its ability to learn simple and effective models. However, most GP methods require a large …

Classifying faces is a difficult task due to image variations in illumination, occlusion, pose,
expression, etc. Typically, it is challenging to build a generalised classifier when the training …