Accurate tool wear prediction is an essential task in machining processes because it helps
to schedule efficient tool maintenance and maximise the tool's useful life, thus contributing to …

The use of machine learning-based techniques has expanded to many areas that require
optimization. One of such area is Integrated Circuit (IC) design and sizing optimization …

Domain Generalization (DG) aims to develop models that can learn from data in source
domains and generalize to unseen target domains. Recently, some domain generalization …

Domain generalization (DG) endeavours to develop robust models that possess strong
generalizability while preserving excellent discriminability. Nonetheless, pivotal DG …

Detecting Liver tumors without contrast agents (CAs) has shown great potential to advance
liver cancer screening. It enables the provision of a reliable liver tumor-detecting result from …

Robust design in analog integrated circuits (ICs) is intricate due to process variations,
culminating in notable performance uncertainties. Contemporary surrogate-based …

Domain generalization (DG) aims to train a model with access to a limited number of source
domains for generalizing it across various unseen target domains. The key to solving the DG …

Automatic brain tumour segmentation in MRI scans aims to separate the brain tumour's
endoscopic core, edema, non‐enhancing tumour core, peritumoral edema, and enhancing …

The identification and restoration of ancient watermarks have long been a major topic in
codicology and history. Classifying historical documents based on watermarks is …

The goal of single domain generalization is to use data from a single domain (source
domain) to train a model, which is then deployed over several unknown domains for testing …