This paper introduces a new neural network language model (NNLM) based on word clustering to structure the output vocabulary: Structured Output Layer NNLM. This model is able to h...
Hai Son Le, Ilya Oparin, Alexandre Allauzen, Jean-...
This paper proposes an on-line error detecting method for a manually annotated corpus using min-max modular (M3 ) neural networks. The basic idea of the method is to use guaranteed...
- Gene regulatory networks allow us to study and understand genes’ roles in biological processes. Among others, regulatory networks help to identify pathway initiator genes and t...
Artificial neural networks can be trained to perform excellently in many application areas. While they can learn from raw data to solve sophisticated recognition and analysis prob...
In this work, a framework for the reconstruction of smooth surface shapes from shading images is presented. The method is based on using a backpropagationbased neural network for ...