We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used w...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Bounded Model Checking (BMC) is one of the most paradigmatic practical applications of Boolean Satisfiability (SAT). The utilization of SAT in model checking has allowed signifi...
: This article addresses the problem of estimating the motion of a camera as it observes the outline (or apparent contour) of a solid bounded by a smooth surface in successive imag...
Yasutaka Furukawa, Amit Sethi, Jean Ponce, David J...
Data reduction plays an important role in machine learning and pattern recognition with a high-dimensional data. In real-world applications data usually exists with hybrid formats...