Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …

Robust principal component analysis (RPCA) via decomposition into low-rank plus sparse
matrices offers a powerful framework for a large variety of applications such as image …

Abstract Machine learning (ML) and its parent technology trend, artificial intelligence (AI),
are deriving novel insights from ever larger and more complex datasets. Efficient and …

Image hashing is an effective technology for extensive image applications, such as retrieval,
authentication and copy detection. This paper designs a new image hashing scheme based …

Principal component analysis (PCA) is a key tool in the field of data dimensionality
reduction. However, some applications involve heterogeneous data that vary in quality due …

Nonmydriatic retinal fundus images often suffer from quality issues and artifacts due to
ocular or systemic comorbidities, leading to potential inaccuracies in clinical diagnoses. In …

The technology of image recovery, as a part of image processing, becomes more and more
important. The robust principle component analysis (RPCA) serves as a key problem for low …

Principal component analysis (PCA) is a key tool in the field of data dimensionality reduction
that is useful for various data science problems. However, many applications involve …

Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …