Euclidean distance matrix completion problem aims at reconstructing the low dimensional geometry structure of nodes given only a few pairwise distances between nodes [1]. This problem arises in many applications including networks and machine learning where much information of points is laking. For instance, in sensor networks, due to the constraints of energy and communication radius, sensor n...

Skeleton extraction and visualization of 3D reconstructed target objects from multiple views continues to be a major challenge in terms of providing intuitive and uncluttered images that allow the users to understand their data. This paper presents a three-dimensional skeleton extraction technique of deformable objects based on a normalized gradient vector flow in order to analyze and visualize...

Abstract We initiate a study of the Euclidean distance degree in context sparse polynomials. Specifically, we consider hypersurface $$f=0$$ f = 0 defined by polynomial f that is general given its support, such support contains origin. show equals mixed ...

Similarity-based retrieval has attracted an increasing amount of attention in recent years. Although there are many different approaches, most are based on a common premise of dimensionality reduction and spatial access methods. Relative change of the time series data provides more meaning and insight view of problem domain.. This paper presents our efforts on considering the relative changes o...