Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
—Many recognition procedures rely on the consistency of a subset of data features with a hypothesis as the sufficient evidence to the presence of the corresponding object. We ana...
Human nonverbal behavior recognition from multiple cues and modalities has attracted a lot of interest in recent years. Despite the interest, many research questions, including th...
Stavros Petridis, Hatice Gunes, Sebastian Kaltwang...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
The design of a general purpose artificial vision system capable of recognizing arbitrarily complex threedimensional objects without human intervention is still a challenging task...