Abstract: Synthetic aperture radar (SAR) data classification has gained significant research interest, as accurate land-cover information is vital in a wide range of planning and management activities ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

A comprehensive, standalone educational resource for learning remote sensing and digital image processing using Google Earth Engine. This course was originally developed at the University of Florida ...

Abstract: Circulating tumor cell (CTC) detection is crucial for reducing cancer mortality and disease burden. Traditional methods rely on the physical or biological properties of CTCs and involve ...

Department of Information Systems, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia. Therefore, further exploration is vital to discover a complete set of risk ...

Cascades of events and extreme occurrences have garnered significant attention across diverse domains like seismology, neuroscience, economics, finance, and other social sciences. Such events may ...

We consider learning a sequence classifier without labeled data by using sequential output statistics. The problem is highly valuable since obtaining labels in training data is often costly, while the ...

Abstract: Many modern classification problems involve data that live in high-dimensional spaces but exhibit strong low-dimensional structure. Motivated by the manifold hypothesis, this talk presents a ...