Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
— The assessment of highly-risky situations at road intersections have been recently revealed as an important research topic within the context of the automotive industry. In thi...
— Neural networks have been proposed as an ideal cognitive modeling methodology to deal with the symbol grounding problem. More recently, such neural network approaches have been...
Abstract. Recurrent neural networks (RNNs) have proved effective at one dimensional sequence learning tasks, such as speech and online handwriting recognition. Some of the properti...
—We have previously developed a neurodynamical model of motion segregation in cortical visual area V1 and MT of the dorsal stream. The model explains how motion ambiguities cause...