Abstract: In supervised classification, many previous methods are model selections or parameters learning, not taking consideration ... Widely used method in computing manifold regularization is ...

If you want to use self-supervised feature extraction ... His research focuses on hyperspectral image processing, computer vision and machine learning. Advisor: Bing Tu (Professor and PhD Supervisor ...

In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning. Whether you're a beginner or brushing up on AI ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

Abstract: The recent success of learning-based algorithms can be greatly ... In this work, we propose SS-StyleGAN, a self-supervised approach for image annotation and classification suitable for ...

Examples of this are the recent hurricanes Otis and John, which hit the state of Guerrero in the space of just two years. Otis arrived in Acapulco in October 2023 as a category 5 hurricane, causing ...