Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, T...
This paper presents a system which learns from examples to automatically recognize people and estimate their poses in image sequences with the potential application to daily surve...
Reliable tracking of multiple moving objects in video is an interesting challenge, made difficult in real-world video by various sources of noise and uncertainty. We propose a Bay...
Recently, several music information retrieval (MIR) systems have been developed which retrieve musical pieces by the user’s singing voice. All of these systems use only the melo...