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...
When a phenomenon is described by a parametric model and multiple datasets are available, a key problem in statistics is to discover which datasets are characterized by the same p...
In recent years the Markov Random Field (MRF) has
become the de facto probabilistic model for low-level vision
applications. However, in a maximum a posteriori
(MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
We consider the problem of estimating the 3D shape and reflectance properties of an object made of a single material from a calibrated set of multiple views. To model reflectance, ...
It is well recognized that novel computational models, devices and technologies are needed in order to sustain the remarkable advancement of CMOS-based VLSI circuits and systems. ...
Xiaobo Sharon Hu, Alexander Khitun, Konstantin K. ...