In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Learning to recognize or predict sequences using long-term context has many applications. However, practical and theoretical problems are found in training recurrent neural networ...
In this paper, we introduce a novel method of automatically finding the training set of RBF networks for morphing a prototype face to represent a new face. This is done by automa...
The Duy Bui, Mannes Poel, Dirk Heylen, Anton Nijho...
: Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and ...
Abstract. Inspired on psycholinguistics and neuroscience, a symbolicconnectionist hybrid system called θ-Pred (Thematic Predictor for natural language) is proposed, designed to re...