This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
We proposed a neural segmentation model that is suitable for implementation in analog VLSIs using conventional CMOS technology. The model consists of neural oscillators mutually co...
Gessyca Maria Tovar, Eric Shun Fukuda, Tetsuya Asa...
This paper presents a technique for the automatic classification of vocal and non-vocal regions in an acoustic musical signal. The proposed technique uses acoustic features which ...
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...