Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...
: Sufficiently high data quality is crucial for almost every application. Nonetheless, data quality issues are nearly omnipresent. The reasons for poor quality cannot simply be bla...
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
3D reconstruction of a dynamic scene from features in two cameras usually requires synchronization and correspondences between the cameras. These may be hard to achieve due to occl...
Progressive loss of the field of vision is characteristic of a number of eye diseases such as glaucoma, a leading cause of irreversible blindness in the world. Recently, there has ...