— A piecewise linear network is discussed which classifies N-dimensional input vectors. The network uses a distance measure to assign incoming input vectors to an appropriate clu...
A. A. Abdurrab, Michael T. Manry, Jiang Li, Sanjee...
We present a method for compressing non-manifold polygonal meshes, i.e., polygonal meshes with singularities, which occur very frequently in the real-world. Most efficient polygon...
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
Video and image datasets can often be described by a small number of parameters, even though each image usually consists of hundreds or thousands of pixels. This observation is of...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...