Self-supervised learning has emerged as a powerful paradigm to bridge the gap between data abundance and label scarcity in medical imaging. By constructing supervisory signals from the data ...

Gain a deeper understanding of artificial intelligence with Machine Learning Fundamentals: Principles and Applications. This course explores core concepts and practical uses of supervised and ...

Aims To develop and validate DeepAdapter, a novel deep learning algorithm that integrates self-supervised learning (SSL) and unsupervised domain adaptation (UDA) to enhance model generalisability for ...