Recent advances in spatio-spectral sampling and panchromatic pixels have contributed to increased spatial resolution and enhanced noise performance. As such, it is necessary to co...
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Many perceptual models and theories hinge on treating objects as a collection of constituent parts. When applying these approaches to data, a fundamental problem arises: how can w...
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...