This paper presents an efficient technique for human motion recognition; in particular, it is focused on labeling a movement as a walking or running displacement, which are the mo...
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
In this paper, we describe development of a mobile robot which does unsupervised learning for recognizing an environment from action sequences. We call this novel recognition appr...
When exposed to environmental noise, speakers adjust their speech production to maintain intelligible communication. This phenomenon, called Lombard effect (LE), is known to consi...
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...